MCP Toolbox for Databases

ADK

Mon, 01 Jan 0001 00:00:00 +0000

Overview

The @toolbox-sdk/adk package provides a Javascript interface to the MCP Toolbox service, enabling you to load and invoke tools from your own applications.

Supported Environments

This SDK is a standard Node.js package built with TypeScript, ensuring broad compatibility with the modern JavaScript ecosystem.

Node.js: Actively supported on Node.js v18.x and higher. The package is compatible with both modern ES Module (import) and legacy CommonJS (require).
TypeScript: The SDK is written in TypeScript and ships with its own type declarations, providing a first-class development experience with autocompletion and type-checking out of the box.
JavaScript: Fully supports modern JavaScript in Node.js environments.

Installation

npm install @toolbox-sdk/adk

Quickstart

Start the Toolbox Service

ADK

Mon, 01 Jan 0001 00:00:00 +0000

Overview

The toolbox-adk package provides a Python interface to the MCP Toolbox service, enabling you to load and invoke tools from your own applications.

Installation

pip install google-adk[toolbox]

Usage

The primary entry point is the ToolboxToolset, which loads tools from a remote Toolbox server and adapts them for use with ADK agents.

Note

alloydb-ai-nl

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-ai-nl tool leverages AlloyDB AI next-generation natural Language support to allow an Agent the ability to query the database directly using natural language. Natural language streamlines the development of generative AI applications by transferring the complexity of converting natural language to SQL from the application layer to the database layer.

AlloyDB AI Natural Language delivers secure and accurate responses for application end user natural language questions. Natural language streamlines the development of generative AI applications by transferring the complexity of converting natural language to SQL from the application layer to the database layer.

alloydb-create-cluster

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-create-cluster tool creates a new AlloyDB for PostgreSQL cluster in a specified project and location.

This tool provisions a cluster with a private IP address within the specified VPC network.

Permissions & APIs Required: Before using, ensure the following on your GCP project:

The AlloyDB API is enabled.
The user or service account executing the tool has one of the following IAM roles:
- roles/alloydb.admin (the AlloyDB Admin predefined IAM role)
- roles/owner (the Owner basic IAM role)
- roles/editor (the Editor basic IAM role)

The tool takes the following input parameters:

alloydb-create-instance

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-create-instance tool creates a new AlloyDB instance (PRIMARY or READ_POOL) within a specified cluster. This tool provisions a new instance with a public IP address.

Permissions & APIs Required: Before using, ensure the following on your GCP project:

The AlloyDB API is enabled.
The user or service account executing the tool has one of the following IAM roles:
- roles/alloydb.admin (the AlloyDB Admin predefined IAM role)
- roles/owner (the Owner basic IAM role)
- roles/editor (the Editor basic IAM role)

The tool takes the following input parameters:

alloydb-get-cluster

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-get-cluster tool retrieves detailed information for a single, specified AlloyDB cluster.

Parameter	Type	Description	Required
`project`	string	The GCP project ID to get cluster for.	Yes
`location`	string	The location of the cluster (e.g., ‘us-central1’).	Yes
`cluster`	string	The ID of the cluster to retrieve.	Yes

Compatible Sources

This tool can be used with the following database sources:

Source Name
AlloyDB Admin

Example

kind: tool
name: get_specific_cluster
type: alloydb-get-cluster
source: my-alloydb-admin-source
description: Use this tool to retrieve details for a specific AlloyDB cluster.

Reference

field	type	required	description
type	string	true	Must be alloydb-get-cluster.
source	string	true	The name of an `alloydb-admin` source.
description	string	false	Description of the tool that is passed to the agent.

alloydb-get-instance

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-get-instance tool retrieves detailed information for a single, specified AlloyDB instance.

Parameter	Type	Description	Required
`project`	string	The GCP project ID to get instance for.	Yes
`location`	string	The location of the instance (e.g., ‘us-central1’).	Yes
`cluster`	string	The ID of the cluster.	Yes
`instance`	string	The ID of the instance to retrieve.	Yes

Compatible Sources

This tool can be used with the following database sources:

Source Name
AlloyDB Admin

Example

kind: tool
name: get_specific_instance
type: alloydb-get-instance
source: my-alloydb-admin-source
description: Use this tool to retrieve details for a specific AlloyDB instance.

Reference

field	type	required	description
type	string	true	Must be alloydb-get-instance.
source	string	true	The name of an `alloydb-admin` source.
description	string	false	Description of the tool that is passed to the agent.

alloydb-get-user

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-get-user tool retrieves detailed information for a single, specified AlloyDB user.

Parameter	Type	Description	Required
`project`	string	The GCP project ID to get user for.	Yes
`location`	string	The location of the cluster (e.g., ‘us-central1’).	Yes
`cluster`	string	The ID of the cluster to retrieve the user from.	Yes
`user`	string	The ID of the user to retrieve.	Yes

Compatible Sources

This tool can be used with the following database sources:

alloydb-list-clusters

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-list-clusters tool retrieves AlloyDB cluster information for all or specified locations in a given project.

alloydb-list-clusters tool lists the detailed information of AlloyDB cluster(cluster name, state, configuration, etc) for a given project and location. The tool takes the following input parameters:

Parameter	Type	Description	Required
`project`	string	The GCP project ID to list clusters for.	Yes
`location`	string	The location to list clusters in (e.g., ‘us-central1’). Use `-` for all locations. Default: `-`.	No

Compatible Sources

This tool can be used with the following database sources:

alloydb-list-instances

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-list-instances tool retrieves AlloyDB instance information for all or specified clusters and locations in a given project.

alloydb-list-instances tool lists the detailed information of AlloyDB instances (instance name, type, IP address, state, configuration, etc) for a given project, cluster and location. The tool takes the following input parameters:

Parameter	Type	Description	Required
`project`	string	The GCP project ID to list instances for.	Yes
`cluster`	string	The ID of the cluster to list instances from. Use ‘-’ to get results for all clusters. Default: `-`.	No
`location`	string	The location of the cluster (e.g., ‘us-central1’). Use ‘-’ to get results for all locations. Default: `-`.	No

Compatible Sources

This tool can be used with the following database sources:

alloydb-list-users

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-list-users tool lists all database users within an AlloyDB cluster.

The tool takes the following input parameters:

Parameter	Type	Description	Required
`project`	string	The GCP project ID to list users for.	Yes
`cluster`	string	The ID of the cluster to list users from.	Yes
`location`	string	The location of the cluster (e.g., ‘us-central1’).	Yes

Compatible Sources

This tool can be used with the following database sources:

Source Name
AlloyDB Admin

Example

kind: tool
name: list_users
type: alloydb-list-users
source: alloydb-admin-source
description: Use this tool to list all database users within an AlloyDB cluster

Reference

field	type	required	description
type	string	true	Must be alloydb-list-users.
source	string	true	The name of an `alloydb-admin` source.
description	string	false	Description of the tool that is passed to the agent.

bigquery-analyze-contribution

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-analyze-contribution tool performs contribution analysis in BigQuery by creating a temporary CONTRIBUTION_ANALYSIS model and then querying it with ML.GET_INSIGHTS to find top contributors for a given metric.

bigquery-analyze-contribution takes the following parameters:

input_data (string, required): The data that contain the test and control data to analyze. This can be a fully qualified BigQuery table ID (e.g., my-project.my_dataset.my_table) or a SQL query that returns the data.
contribution_metric (string, required): The name of the column that contains the metric to analyze. This can be SUM(metric_column_name), SUM(numerator_metric_column_name)/SUM(denominator_metric_column_name) or SUM(metric_sum_column_name)/COUNT(DISTINCT categorical_column_name) depending the type of metric to analyze.
is_test_col (string, required): The name of the column that identifies whether a row is in the test or control group. The column must contain boolean values.
dimension_id_cols (array of strings, optional): An array of column names that uniquely identify each dimension.
top_k_insights_by_apriori_support (integer, optional): The number of top insights to return, ranked by apriori support. Default to ‘30’.
pruning_method (string, optional): The method to use for pruning redundant insights. Can be 'NO_PRUNING' or 'PRUNE_REDUNDANT_INSIGHTS'. Defaults to 'PRUNE_REDUNDANT_INSIGHTS'.

The behavior of this tool is influenced by the writeMode setting on its bigquery source:

bigquery-conversational-analytics

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-conversational-analytics tool allows you to ask questions about your data in natural language.

This function takes a user’s question (which can include conversational history for context) and references to specific BigQuery tables, and sends them to a stateless conversational API.

The API uses a GenAI agent to understand the question, generate and execute SQL queries and Python code, and formulate an answer. This function returns a detailed, sequential log of this entire process, which includes any generated SQL or Python code, the data retrieved, and the final text answer.

bigquery-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-execute-sql tool executes a SQL statement against BigQuery.

bigquery-execute-sql accepts the following parameters:

sql (required): The GoogleSQL statement to execute.
dry_run (optional): If set to true, the query is validated but not run, returning information about the execution instead. Defaults to false.

The behavior of this tool is influenced by the writeMode setting on its bigquery source:

allowed (default): All SQL statements are permitted.
blocked: Only SELECT statements are allowed. Any other type of statement (e.g., INSERT, UPDATE, CREATE) will be rejected.
protected: This mode enables session-based execution. SELECT statements can be used on all tables, while write operations are allowed only for the session’s temporary dataset (e.g., CREATE TEMP TABLE ...). This prevents modifications to permanent datasets while allowing stateful, multi-step operations within a secure session.

The tool’s behavior is influenced by the allowedDatasets restriction on the bigquery source. Similar to writeMode, this setting provides an additional layer of security by controlling which datasets can be accessed:

bigquery-forecast

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-forecast tool forecasts time series data in BigQuery.

bigquery-forecast constructs and executes a SELECT * FROM AI.FORECAST(...) query based on the provided parameters:

history_data (string, required): This specifies the source of the historical time series data. It can be either a fully qualified BigQuery table ID (e.g., my-project.my_dataset.my_table) or a SQL query that returns the data.
timestamp_col (string, required): The name of the column in your history_data that contains the timestamps.
data_col (string, required): The name of the column in your history_data that contains the numeric values to be forecasted.
id_cols (array of strings, optional): If you are forecasting multiple time series at once (e.g., sales for different products), this parameter takes an array of column names that uniquely identify each series. It defaults to an empty array if not provided.
horizon (integer, optional): The number of future time steps you want to predict. It defaults to 10 if not specified.

The behavior of this tool is influenced by the writeMode setting on its bigquery source:

bigquery-get-dataset-info

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-get-dataset-info tool retrieves metadata for a BigQuery dataset.

bigquery-get-dataset-info accepts the following parameters:

dataset (required): Specifies the dataset for which to retrieve metadata.
project (optional): Defines the Google Cloud project ID. If not provided, the tool defaults to the project from the source configuration.

The tool’s behavior regarding these parameters is influenced by the allowedDatasets restriction on the bigquery source:

Without allowedDatasets restriction: The tool can retrieve metadata for any dataset specified by the dataset and project parameters.
With allowedDatasets restriction: Before retrieving metadata, the tool verifies that the requested dataset is in the allowed list. If it is not, the request is denied. If only one dataset is specified in the allowedDatasets list, it will be used as the default value for the dataset parameter.

Compatible Sources

This tool can be used with the following database sources:

bigquery-get-table-info

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-get-table-info tool retrieves metadata for a BigQuery table.

bigquery-get-table-info accepts the following parameters:

table (required): The name of the table for which to retrieve metadata.
dataset (required): The dataset containing the specified table.
project (optional): The Google Cloud project ID. If not provided, the tool defaults to the project from the source configuration.

The tool’s behavior regarding these parameters is influenced by the allowedDatasets restriction on the bigquery source:

bigquery-list-dataset-ids

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-list-dataset-ids tool returns all dataset IDs from the source.

bigquery-list-dataset-ids accepts the following parameter:

project (optional): Defines the Google Cloud project ID. If not provided, the tool defaults to the project from the source configuration.

The tool’s behavior regarding this parameter is influenced by the allowedDatasets restriction on the bigquery source:

Without allowedDatasets restriction: The tool can list datasets from any project specified by the project parameter.
With allowedDatasets restriction: The tool directly returns the pre-configured list of dataset IDs from the source, and the project parameter is ignored.

Compatible Sources

This tool can be used with the following database sources:

bigquery-list-table-ids

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-list-table-ids tool returns table IDs in a given BigQuery dataset.

bigquery-list-table-ids accepts the following parameters:

dataset (required): Specifies the dataset from which to list table IDs.
project (optional): Defines the Google Cloud project ID. If not provided, the tool defaults to the project from the source configuration.

The tool’s behavior regarding these parameters is influenced by the allowedDatasets restriction on the bigquery source:

Without allowedDatasets restriction: The tool can list tables from any dataset specified by the dataset and project parameters.
With allowedDatasets restriction: Before listing tables, the tool verifies that the requested dataset is in the allowed list. If it is not, the request is denied. If only one dataset is specified in the allowedDatasets list, it will be used as the default value for the dataset parameter.

Compatible Sources

This tool can be used with the following database sources:

bigquery-search-catalog

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-search-catalog tool returns all entries in Dataplex Catalog (e.g. tables, views, models) with system=bigquery that matches given user query.

bigquery-search-catalog takes a required query parameter based on which entries are filtered and returned to the user. It also optionally accepts following parameters:

datasetIds - The IDs of the bigquery dataset.
projectIds - The IDs of the bigquery project.
types - The type of the data. Accepted values are: CONNECTION, POLICY, DATASET, MODEL, ROUTINE, TABLE, VIEW.
pageSize - Number of results in the search page. Defaults to 5.

Compatible Sources

This tool can be used with the following database sources:

bigquery-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigquery-sql tool executes a pre-defined SQL statement.

The behavior of this tool is influenced by the writeMode setting on its bigquery source:

allowed (default) and blocked: These modes do not impose any restrictions on the bigquery-sql tool. The pre-defined SQL statement will be executed as-is.
protected: This mode enables session-based execution. The tool will operate within the same BigQuery session as other tools using the same source, allowing it to interact with temporary resources like TEMP tables created within that session.

Compatible Sources

This tool can be used with the following database sources:

bigtable-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A bigtable-sql tool executes a pre-defined SQL statement against a Bigtable instance.

GoogleSQL

Bigtable supports SQL queries. The integration with Toolbox supports googlesql dialect, the specified SQL statement is executed as a data manipulation language (DML) statements, and specified parameters will inserted according to their name: e.g. @name.

Note

cassandra-cql

Mon, 01 Jan 0001 00:00:00 +0000

About

A cassandra-cql tool executes a pre-defined CQL statement against a Cassandra database.

The specified CQL statement is executed as a prepared statement, and expects parameters in the CQL query to be in the form of placeholders ?.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cassandra

Example

Note: This tool uses parameterized queries to prevent CQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for keyspaces, table names, column names, or other parts of the query.

CLI

Mon, 01 Jan 0001 00:00:00 +0000

Reference

Flag (Short)	Flag (Long)	Description	Default
`-a`	`--address`	Address of the interface the server will listen on.	`127.0.0.1`
	`--disable-reload`	Disables dynamic reloading config.
`-h`	`--help`	help for toolbox
	`--log-level`	Specify the minimum level logged. Allowed: ‘DEBUG’, ‘INFO’, ‘WARN’, ‘ERROR’.	`info`
	`--logging-format`	Specify logging format to use. Allowed: ‘standard’ or ‘JSON’.	`standard`
`-p`	`--port`	Port the server will listen on.	`5000`
	`--prebuilt`	Use one or more prebuilt tool configuration by source type. See Prebuilt Tools Reference for allowed values.
	`--stdio`	Listens via MCP STDIO instead of acting as a remote HTTP server.
	`--telemetry-gcp`	Enable exporting directly to Google Cloud Monitoring.
	`--telemetry-otlp`	Enable exporting using OpenTelemetry Protocol (OTLP) to the specified endpoint (e.g. ‘http://127.0.0.1:4318’)
	`--telemetry-service-name`	Sets the value of the service.name resource attribute for telemetry data.	`toolbox`
	`--config`	File path specifying the tool configuration. Cannot be used with –configs or –config-folder.
	`--configs`	Multiple file paths specifying tool configurations. Files will be merged. Cannot be used with –config or –config-folder.
	`--config-folder`	Directory path containing YAML tool configuration files. All .yaml and .yml files in the directory will be loaded and merged. Cannot be used with –config or –configs.
	`--ui`	Launches the Toolbox UI web server.
	`--allowed-origins`	Specifies a list of origins permitted to access this server for CORs access.	`*`
	`--allowed-hosts`	Specifies a list of hosts permitted to access this server to prevent DNS rebinding attacks.	`*`
	`--user-agent-metadata`	Appends additional metadata to the User-Agent.
	`--poll-interval`	Specifies the polling frequency (seconds) for configuration file updates.	`0`
`-v`	`--version`	version for toolbox

Sub Commands

invoke

Executes a tool directly with the provided parameters. This is useful for testing tool configurations and parameters without needing a full client setup.

clickhouse-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A clickhouse-execute-sql tool executes a SQL statement against a ClickHouse database.

clickhouse-execute-sql takes one input parameter sql and runs the SQL statement against the specified source. This tool includes query logging capabilities for monitoring and debugging purposes.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
ClickHouse

Parameters

parameter	type	required	description
sql	string	true	The SQL statement to execute against the database

Example

kind: tool
name: execute_sql_tool
type: clickhouse-execute-sql
source: my-clickhouse-instance
description: Use this tool to execute SQL statements against ClickHouse.

Reference

field	type	required	description
type	string	true	Must be “clickhouse-execute-sql”.
source	string	true	Name of the ClickHouse source to execute SQL against.
description	string	true	Description of the tool that is passed to the LLM.

cloud-gemini-data-analytics-query

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-gemini-data-analytics-query tool allows you to send natural language questions to the Gemini Data Analytics API and receive structured responses containing SQL queries, natural language answers, and explanations. For details on defining data agent context for database data sources, see the official documentation.

[!NOTE] Only alloydb, spannerReference, and cloudSqlReference are supported as datasource references.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Gemini Data Analytics

Example

kind: tool
name: my-gda-query-tool
type: cloud-gemini-data-analytics-query
source: my-gda-source
description: "Use this tool to send natural language queries to the Gemini Data Analytics API and receive SQL, natural language answers, and explanations."
location: ${your_database_location}
context:
 datasourceReferences:
 cloudSqlReference:
 databaseReference:
 projectId: "${your_project_id}"
 region: "${your_database_instance_region}"
 instanceId: "${your_database_instance_id}"
 databaseId: "${your_database_name}"
 engine: "POSTGRESQL"
 agentContextReference:
 contextSetId: "${your_context_set_id}" # E.g. projects/${project_id}/locations/${context_set_location}/contextSets/${context_set_id}
generationOptions:
 generateQueryResult: true
 generateNaturalLanguageAnswer: true
 generateExplanation: true
 generateDisambiguationQuestion: true

Usage Flow

When using this tool, a query parameter containing a natural language query is provided to the tool (typically by an agent). The tool then interacts with the Gemini Data Analytics API using the context defined in your configuration.

cloud-healthcare-fhir-fetch-page

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-fhir-fetch-page tool fetches a page of FHIR resources from a given URL.

cloud-healthcare-fhir-fetch-page can be used for pagination when a previous tool call (like cloud-healthcare-fhir-patient-search or cloud-healthcare-fhir-patient-everything) returns a ’next’ link in the response bundle.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: get_fhir_store
type: cloud-healthcare-fhir-fetch-page
source: my-healthcare-source
description: Use this tool to fetch a page of FHIR resources from a FHIR Bundle's entry.link.url

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-fhir-fetch-page”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
pageURL	string	true	The full URL of the FHIR page to fetch. This would usually be the value of `Bundle.entry.link.url` field within the response returned from FHIR search or FHIR patient everything operations.

cloud-healthcare-fhir-patient-everything

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-fhir-patient-everything tool retrieves resources related to a given patient from a FHIR store.

cloud-healthcare-fhir-patient-everything returns all the information available for a given patient ID. It can be configured to only return certain resource types, or only resources that have been updated after a given time.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: fhir_patient_everything
type: cloud-healthcare-fhir-patient-everything
source: my-healthcare-source
description: Use this tool to retrieve all the information about a given patient.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-fhir-patient-everything”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
patientID	string	true	The ID of the patient FHIR resource for which the information is required.
resourceTypesFilter	string	false	String of comma-delimited FHIR resource types. If provided, only resources of the specified resource type(s) are returned.
sinceFilter	string	false	If provided, only resources updated after this time are returned. The time uses the format YYYY-MM-DDThh:mm:ss.sss+zz:zz. The time must be specified to the second and include a time zone. For example, 2015-02-07T13:28:17.239+02:00 or 2017-01-01T00:00:00Z.
storeID	string	true*	The FHIR store ID to search in.

*If the allowedFHIRStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-fhir-patient-search

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-fhir-patient-search tool searches for patients in a FHIR store based on a set of criteria.

cloud-healthcare-fhir-patient-search returns a list of patients that match the given criteria.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: fhir_patient_search
type: cloud-healthcare-fhir-patient-search
source: my-healthcare-source
description: Use this tool to search for patients in the FHIR store.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-fhir-patient-search”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
active	string	false	Whether the patient record is active.
city	string	false	The city of the patient’s address.
country	string	false	The country of the patient’s address.
postalcode	string	false	The postal code of the patient’s address.
state	string	false	The state of the patient’s address.
addressSubstring	string	false	A substring to search for in any address field.
birthDateRange	string	false	A date range for the patient’s birth date in the format YYYY-MM-DD/YYYY-MM-DD.
deathDateRange	string	false	A date range for the patient’s death date in the format YYYY-MM-DD/YYYY-MM-DD.
deceased	string	false	Whether the patient is deceased.
email	string	false	The patient’s email address.
gender	string	false	The patient’s gender.
addressUse	string	false	The use of the patient’s address.
name	string	false	The patient’s name.
givenName	string	false	A portion of the given name of the patient.
familyName	string	false	A portion of the family name of the patient.
phone	string	false	The patient’s phone number.
language	string	false	The patient’s preferred language.
identifier	string	false	An identifier for the patient.
summary	boolean	false	Requests the server to return a subset of the resource. True by default.
storeID	string	true*	The FHIR store ID to search in.

*If the allowedFHIRStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-get-dataset

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-get-dataset tool retrieves metadata for a Healthcare dataset.

cloud-healthcare-get-dataset returns the metadata of the healthcare dataset configured in the source. It takes no extra parameters.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: get_dataset
type: cloud-healthcare-get-dataset
source: my-healthcare-source
description: Use this tool to get healthcare dataset metadata.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-get-dataset”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

cloud-healthcare-get-dicom-store

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-get-dicom-store tool retrieves information about a DICOM store.

cloud-healthcare-get-dicom-store returns the details of a DICOM store.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: get_dicom_store
type: cloud-healthcare-get-dicom-store
source: my-healthcare-source
description: Use this tool to get information about a DICOM store.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-get-dicom-store”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
storeID	string	true*	The DICOM store ID to get details for.

*If the allowedDICOMStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-get-dicom-store-metrics

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-get-dicom-store-metrics tool retrieves metrics for a DICOM store.

cloud-healthcare-get-dicom-store-metrics returns the metrics of a DICOM store.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: get_dicom_store_metrics
type: cloud-healthcare-get-dicom-store-metrics
source: my-healthcare-source
description: Use this tool to get metrics for a DICOM store.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-get-dicom-store-metrics”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
storeID	string	true*	The DICOM store ID to get metrics for.

*If the allowedDICOMStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-get-fhir-resource

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-get-fhir-resource tool retrieves a specific FHIR resource from a FHIR store.

cloud-healthcare-get-fhir-resource returns a single FHIR resource, identified by its type and ID.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: get_fhir_resource
type: cloud-healthcare-get-fhir-resource
source: my-healthcare-source
description: Use this tool to retrieve a specific FHIR resource.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-get-fhir-resource”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
resourceType	string	true	The FHIR resource type to retrieve (e.g., Patient, Observation).
resourceID	string	true	The ID of the FHIR resource to retrieve.
storeID	string	true*	The FHIR store ID to retrieve the resource from.

*If the allowedFHIRStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-get-fhir-store

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-get-fhir-store tool retrieves information about a FHIR store.

cloud-healthcare-get-fhir-store returns the details of a FHIR store.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: get_fhir_store
type: cloud-healthcare-get-fhir-store
source: my-healthcare-source
description: Use this tool to get information about a FHIR store.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-get-fhir-store”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
storeID	string	true*	The FHIR store ID to get details for.

*If the allowedFHIRStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-get-fhir-store-metrics

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-get-fhir-store-metrics tool retrieves metrics for a FHIR store.

cloud-healthcare-get-fhir-store-metrics returns the metrics of a FHIR store.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: get_fhir_store_metrics
type: cloud-healthcare-get-fhir-store-metrics
source: my-healthcare-source
description: Use this tool to get metrics for a FHIR store.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-get-fhir-store-metrics”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
storeID	string	true*	The FHIR store ID to get metrics for.

*If the allowedFHIRStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-list-dicom-stores

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-list-dicom-stores lists the available DICOM stores in the healthcare dataset.

cloud-healthcare-list-dicom-stores returns the details of the available DICOM stores in the dataset of the healthcare source. It takes no extra parameters.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: list_dicom_stores
type: cloud-healthcare-list-dicom-stores
source: my-healthcare-source
description: Use this tool to list DICOM stores in the healthcare dataset.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-list-dicom-stores”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

cloud-healthcare-list-fhir-stores

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-list-fhir-stores lists the available FHIR stores in the healthcare dataset.

cloud-healthcare-list-fhir-stores returns the details of the available FHIR stores in the dataset of the healthcare source. It takes no extra parameters.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: list_fhir_stores
type: cloud-healthcare-list-fhir-stores
source: my-healthcare-source
description: Use this tool to list FHIR stores in the healthcare dataset.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-list-fhir-stores”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

cloud-healthcare-retrieve-rendered-dicom-instance

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-retrieve-rendered-dicom-instance tool retrieves a rendered DICOM instance from a DICOM store.

cloud-healthcare-retrieve-rendered-dicom-instance returns a base64 encoded string of the image in JPEG format.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: retrieve_rendered_dicom_instance
type: cloud-healthcare-retrieve-rendered-dicom-instance
source: my-healthcare-source
description: Use this tool to retrieve a rendered DICOM instance from the DICOM store.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-retrieve-rendered-dicom-instance”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
StudyInstanceUID	string	true	The UID of the DICOM study.
SeriesInstanceUID	string	true	The UID of the DICOM series.
SOPInstanceUID	string	true	The UID of the SOP instance.
FrameNumber	integer	false	The frame number to retrieve (1-based). Only applicable to multi-frame instances. Defaults to 1.
storeID	string	true*	The DICOM store ID to retrieve from.

*If the allowedDICOMStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-search-dicom-instances

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-search-dicom-instances tool searches for DICOM instances in a DICOM store based on a set of criteria.

search-dicom-instances returns a list of DICOM instances that match the given criteria.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: search_dicom_instances
type: cloud-healthcare-search-dicom-instances
source: my-healthcare-source
description: Use this tool to search for DICOM instances in the DICOM store.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-search-dicom-instances”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
StudyInstanceUID	string	false	The UID of the DICOM study.
PatientName	string	false	The name of the patient.
PatientID	string	false	The ID of the patient.
AccessionNumber	string	false	The accession number of the study.
ReferringPhysicianName	string	false	The name of the referring physician.
StudyDate	string	false	The date of the study in the format `YYYYMMDD`. You can also specify a date range in the format `YYYYMMDD-YYYYMMDD`.
SeriesInstanceUID	string	false	The UID of the DICOM series.
Modality	string	false	The modality of the series.
SOPInstanceUID	string	false	The UID of the SOP instance.
fuzzymatching	boolean	false	Whether to enable fuzzy matching for patient names. Fuzzy matching will perform tokenization and normalization of both the value of PatientName in the query and the stored value. It will match if any search token is a prefix of any stored token. For example, if PatientName is “John^Doe”, then “jo”, “Do” and “John Doe” will all match. However “ohn” will not match.
includefield	[]string	false	List of attributeIDs to include in the output, such as DICOM tag IDs or keywords. Set to `["all"]` to return all available tags.
storeID	string	true*	The DICOM store ID to search in.

*If the allowedDICOMStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-search-dicom-series

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-search-dicom-series tool searches for DICOM series in a DICOM store based on a set of criteria.

cloud-healthcare-search-dicom-series returns a list of DICOM series that match the given criteria.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: search_dicom_series
type: cloud-healthcare-search-dicom-series
source: my-healthcare-source
description: Use this tool to search for DICOM series in the DICOM store.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-search-dicom-series”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
StudyInstanceUID	string	false	The UID of the DICOM study.
PatientName	string	false	The name of the patient.
PatientID	string	false	The ID of the patient.
AccessionNumber	string	false	The accession number of the study.
ReferringPhysicianName	string	false	The name of the referring physician.
StudyDate	string	false	The date of the study in the format `YYYYMMDD`. You can also specify a date range in the format `YYYYMMDD-YYYYMMDD`.
SeriesInstanceUID	string	false	The UID of the DICOM series.
Modality	string	false	The modality of the series.
fuzzymatching	boolean	false	Whether to enable fuzzy matching for patient names. Fuzzy matching will perform tokenization and normalization of both the value of PatientName in the query and the stored value. It will match if any search token is a prefix of any stored token. For example, if PatientName is “John^Doe”, then “jo”, “Do” and “John Doe” will all match. However “ohn” will not match.
includefield	[]string	false	List of attributeIDs to include in the output, such as DICOM tag IDs or keywords. Set to `["all"]` to return all available tags.
storeID	string	true*	The DICOM store ID to search in.

*If the allowedDIComStores in the source has length 1, then the storeID parameter is not needed.

cloud-healthcare-search-dicom-studies

Mon, 01 Jan 0001 00:00:00 +0000

About

A cloud-healthcare-search-dicom-studies tool searches for DICOM studies in a DICOM store based on a set of criteria.

cloud-healthcare-search-dicom-studies returns a list of DICOM studies that match the given criteria.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Healthcare

Example

kind: tool
name: search_dicom_studies
type: cloud-healthcare-search-dicom-studies
source: my-healthcare-source
description: Use this tool to search for DICOM studies in the DICOM store.

Reference

field	type	required	description
type	string	true	Must be “cloud-healthcare-search-dicom-studies”.
source	string	true	Name of the healthcare source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

field	type	required	description
StudyInstanceUID	string	false	The UID of the DICOM study.
PatientName	string	false	The name of the patient.
PatientID	string	false	The ID of the patient.
AccessionNumber	string	false	The accession number of the study.
ReferringPhysicianName	string	false	The name of the referring physician.
StudyDate	string	false	The date of the study in the format `YYYYMMDD`. You can also specify a date range in the format `YYYYMMDD-YYYYMMDD`.
fuzzymatching	boolean	false	Whether to enable fuzzy matching for patient names. Fuzzy matching will perform tokenization and normalization of both the value of PatientName in the query and the stored value. It will match if any search token is a prefix of any stored token. For example, if PatientName is “John^Doe”, then “jo”, “Do” and “John Doe” will all match. However “ohn” will not match.
includefield	[]string	false	List of attributeIDs to include in the output, such as DICOM tag IDs or keywords. Set to `["all"]` to return all available tags.
storeID	string	true*	The DICOM store ID to search in.

*If the allowedDICOMStores in the source has length 1, then the storeID parameter is not needed.

cloud-monitoring-query-prometheus

Mon, 01 Jan 0001 00:00:00 +0000

The cloud-monitoring-query-prometheus tool fetches timeseries metrics data from Google Cloud Monitoring for a project using a given prometheus query.

About

The cloud-monitoring-query-prometheus tool allows you to query all metrics available in Google Cloud Monitoring using the Prometheus Query Language (PromQL).

Use Cases

Ad-hoc analysis: Quickly investigate performance issues by executing direct promql queries for a database instance.
Prebuilt Configs: Use the already added prebuilt tools mentioned in prebuilt-tools.md to query the databases system/query level metrics.

Here are some common use cases for the cloud-monitoring-query-prometheus tool:

cloud-sql-list-databases

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-list-databases tool lists all Cloud SQL databases in a specified Google Cloud project and instance.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Parameters

The cloud-sql-list-databases tool has two required parameters:

field	type	required	description
project	string	true	The Google Cloud project ID.
instance	string	true	The Cloud SQL instance ID.

Example

Here is an example of how to configure the cloud-sql-list-databases tool in your tools.yaml file:

cloud-sql-list-instances

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-list-instances tool lists all Cloud SQL instances in a specified Google Cloud project.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Parameters

The cloud-sql-list-instances tool has one required parameter:

field	type	required	description
project	string	true	The Google Cloud project ID.

Example

Here is an example of how to configure the cloud-sql-list-instances tool in your tools.yaml file:

kind: source
name: my-cloud-sql-admin-source
type: cloud-sql-admin
---
kind: tool
name: list_my_instances
type: cloud-sql-list-instances
source: my-cloud-sql-admin-source
description: Use this tool to list all Cloud SQL instances in a project.

Reference

field	type	required	description
type	string	true	Must be “cloud-sql-list-instances”.
description	string	false	Description of the tool that is passed to the agent.
source	string	true	The name of the `cloud-sql-admin` source to use for this tool.

cockroachdb-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A cockroachdb-execute-sql tool executes ad-hoc SQL statements against a CockroachDB database. This tool is designed for interactive workflows where the SQL query is provided dynamically at runtime, making it ideal for developer assistance and exploratory data analysis.

The tool takes a single sql parameter containing the SQL statement to execute and returns the query results.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents. For production use cases with predefined queries, use cockroachdb-sql instead.

cockroachdb-list-schemas

Mon, 01 Jan 0001 00:00:00 +0000

About

The cockroachdb-list-schemas tool retrieves a list of schemas (namespaces) in a CockroachDB database. Schemas are used to organize database objects such as tables, views, and functions into logical groups.

This tool is useful for:

Understanding database organization
Discovering available schemas
Multi-tenant application analysis
Schema-level access control planning

Compatible Sources

This tool can be used with the following database sources:

Source Name
CockroachDB

Requirements

To list schemas, the user needs:

cockroachdb-list-tables

Mon, 01 Jan 0001 00:00:00 +0000

About

The cockroachdb-list-tables tool retrieves a list of tables from a CockroachDB database. It provides detailed information about table structure, including columns, constraints, indexes, and foreign key relationships.

This tool is useful for:

Database schema discovery
Understanding table relationships
Generating context for AI-powered database queries
Documentation and analysis

Compatible Sources

This tool can be used with the following database sources:

Source Name
CockroachDB

Parameters

The tool accepts optional runtime parameters:

cockroachdb-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

The cockroachdb-sql tool allows you to execute parameterized SQL queries against a CockroachDB database. This tool supports prepared statements with parameter binding, template parameters for dynamic query construction, and automatic transaction retry for resilience against serialization conflicts.

Compatible Sources

This tool can be used with the following database sources:

Source Name
CockroachDB

Parameters

Parameters allow you to safely pass values into your SQL queries using prepared statements. CockroachDB uses PostgreSQL-style parameter placeholders: $1, $2, etc.

couchbase-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A couchbase-sql tool executes a pre-defined SQL statement against a Couchbase database.

The specified SQL statement is executed as a parameterized statement, and specified parameters will be used according to their name: e.g. $id.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Couchbase

Example

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

dataform-compile-local

Mon, 01 Jan 0001 00:00:00 +0000

About

A dataform-compile-local tool runs the dataform compile command on a local Dataform project.

It is a standalone tool and is not compatible with any sources.

At invocation time, the tool executes dataform compile --json in the specified project directory and returns the resulting JSON object from the CLI.

dataform-compile-local takes the following parameter:

project_dir (string): The absolute or relative path to the local Dataform project directory. The server process must have read access to this path.

Requirements

Dataform CLI

This tool executes the dataform command-line interface (CLI) via a system call. You must have the dataform CLI installed and available in the server’s system PATH.

dataplex-lookup-context

Mon, 01 Jan 0001 00:00:00 +0000

About

A dataplex-lookup-context tool provides rich metadata of one or more data assets along with their relationships.

dataplex-lookup-context takes a required name parameter which contains the project and location to which the request should be attributed in the following form: projects/{project}/locations/{location} and also a required resources parameter which is a list of resource names for which metadata is needed in the following form: projects/{project}/locations/{location}/entryGroups/{group}/entries/{entry}

Compatible Sources

This tool can be used with the following database sources:

dataplex-lookup-entry

Mon, 01 Jan 0001 00:00:00 +0000

About

A dataplex-lookup-entry tool returns details of a particular entry in Dataplex Catalog.

dataplex-lookup-entry takes a required name parameter which contains the project and location to which the request should be attributed in the following form: projects/{project}/locations/{location} and also a required entry parameter which is the resource name of the entry in the following form: projects/{project}/locations/{location}/entryGroups/{entryGroup}/entries/{entry}. It also optionally accepts following parameters:

view - View to control which parts of an entry the service should return. It takes integer values from 1-4 corresponding to type of view - BASIC, FULL, CUSTOM, ALL
aspectTypes - Limits the aspects returned to the provided aspect types in the format projects/{project}/locations/{location}/aspectTypes/{aspectType}. It only works for CUSTOM view.
paths - Limits the aspects returned to those associated with the provided paths within the Entry. It only works for CUSTOM view.

Compatible Sources

This tool can be used with the following database sources:

dataplex-search-aspect-types

Mon, 01 Jan 0001 00:00:00 +0000

About

A dataplex-search-aspect-types tool allows to fetch the metadata template of aspect types based on search query.

dataplex-search-aspect-types accepts following parameters optionally:

query - Narrows down the search of aspect types to value of this parameter. If not provided, it fetches all aspect types available to the user.
pageSize - Number of returned aspect types in the search page. Defaults to 5.
orderBy - Specifies the ordering of results. Supported values are: relevance (default), last_modified_timestamp, last_modified_timestamp asc.

Compatible Sources

This tool can be used with the following database sources:

dataplex-search-entries

Mon, 01 Jan 0001 00:00:00 +0000

About

A dataplex-search-entries tool returns all entries in Dataplex Catalog (e.g. tables, views, models) that matches given user query.

dataplex-search-entries takes a required query parameter based on which entries are filtered and returned to the user. It also optionally accepts following parameters:

scope - A scope limits the search space to a particular project or organization. It must be in the format: organizations/<org_id> or projects/<project_id> or projects/<project_number>.
pageSize - Number of results in the search page. Defaults to 5.
orderBy - Specifies the ordering of results. Supported values are: relevance (default), last_modified_timestamp, last_modified_timestamp asc.

Compatible Sources

This tool can be used with the following database sources:

dataproc-get-cluster

Mon, 01 Jan 0001 00:00:00 +0000

About

A dataproc-get-cluster tool retrieves a specific Dataproc cluster from a Google Cloud Dataproc source.

dataproc-get-cluster accepts the following parameters:

clusterName The short name of the cluster to retrieve. e.g. for projects/my-project/regions/us-central1/clusters/my-cluster, pass my-cluster.

The tool gets the project and region from the source configuration.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Dataproc Clusters

Example

kind: tool
name: get_cluster
type: dataproc-get-cluster
source: my-dataproc-source
description: Use this tool to get details of a Dataproc cluster.

Output Format

{
 "cluster": {
 "name": "projects/my-project/regions/us-central1/clusters/my-cluster",
 "uuid": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
 "state": "RUNNING",
 "createTime": "2023-10-27T10:00:00Z",
 },
 "consoleUrl": "https://console.cloud.google.com/dataproc/clusters/my-cluster/monitoring?region=us-central1&project=my-project",
 "logsUrl": "https://console.cloud.google.com/logs/viewer?advancedFilter=resource.type%3D%22cloud_dataproc_cluster%22%0Aresource.labels.project_id%3D%22my-project%22%0Aresource.labels.region%3D%22us-central1%22%0Aresource.labels.cluster_name%3D%22my-cluster%22%0Aresource.labels.cluster_uuid%3D%22a1b2c3d4-e5f6-7890-1234-567890abcdef%22&project=my-project&resource=cloud_dataproc_cluster%2Fcluster_name%2Fmy-cluster"
}

Reference

field	type	required	description
type	string	true	Must be “dataproc-get-cluster”.
source	string	true	Name of the source the tool should use.
description	string	true	Description of the tool that is passed to the LLM.
authRequired	string[]	false	List of auth services required to invoke this tool

dataproc-get-job

Mon, 01 Jan 0001 00:00:00 +0000

About

A dataproc-get-job tool retrieves a specific Dataproc job from a Google Cloud Dataproc source.

dataproc-get-job accepts the following parameters:

jobId The job ID, e.g. for projects/my-project/regions/us-central1/jobs/my-job, pass my-job.

The tool gets the project and region from the source configuration.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Dataproc Clusters

Example

kind: tool
name: get_job
type: dataproc-get-job
source: my-dataproc-source
description: Use this tool to get details of a Dataproc job.

Output Format

{
 "job": {
 "reference": {
 "projectId": "my-project",
 "jobId": "my-job"
 },
 "placement": {
 "clusterName": "my-cluster",
 "clusterUuid": "a1b2c3d4-e5f6-7890-1234-567890abcdef"
 },
 ...
 },
 "consoleUrl": "https://console.cloud.google.com/dataproc/jobs/my-job?region=us-central1&project=my-project",
 "logsUrl": "https://console.cloud.google.com/logs/viewer?advancedFilter=resource.type%3D%22cloud_dataproc_cluster%22%0Aresource.labels.project_id%3D%22my-project%22%0Aresource.labels.region%3D%22us-central1%22%0Aresource.labels.cluster_name%3D%22my-cluster%22%0Alabels.job_id%3D%22my-job%22&project=my-project&resource=cloud_dataproc_cluster%2Fcluster_name%2Fmy-cluster"
}

Reference

field	type	required	description
type	string	true	Must be “dataproc-get-job”.
source	string	true	Name of the source the tool should use.
description	string	true	Description of the tool that is passed to the LLM.
authRequired	string[]	false	List of auth services required to invoke this tool

dataproc-list-clusters

Mon, 01 Jan 0001 00:00:00 +0000

About

A dataproc-list-clusters tool returns a list of Dataproc clusters from a Google Cloud Dataproc source.

dataproc-list-clusters accepts the following parameters:

filter (optional): A filter expression to limit the clusters returned. Filters are case sensitive and may contain multiple clauses combined with logical operators (AND only). Supported fields are status.state, clusterName, and labels. For example: status.state = ACTIVE AND clusterName = mycluster. Supported status.state values are: ACTIVE, INACTIVE, CREATING, RUNNING, ERROR, DELETING, UPDATING, STOPPING, STOPPED.
pageSize (optional): The maximum number of clusters to return in a single page.
pageToken (optional): A page token, received from a previous call, to retrieve the next page of results. Defaults to 20.

The tool gets the project and region from the source configuration.

dataproc-list-jobs

Mon, 01 Jan 0001 00:00:00 +0000

About

A dataproc-list-jobs tool returns a list of Dataproc jobs from a Google Cloud Dataproc source.

dataproc-list-jobs accepts the following parameters:

filter (optional): A filter expression to limit the jobs returned. Filters are case sensitive and may contain multiple clauses combined with logical operators (AND only). Supported fields are status.state and labels. For example: status.state = RUNNING AND labels.env = production. Supported status.state values are: PENDING, RUNNING, CANCEL_PENDING, JOB_STATE_CANCELLED, DONE, ERROR, ATTEMPT_FAILURE.
jobStateMatcher (optional): Specifies if the job state matcher should match ALL jobs, only ACTIVE jobs, or only NON_ACTIVE jobs. Defaults to ALL. Supported values: ALL, ACTIVE, NON_ACTIVE.
pageSize (optional): The maximum number of jobs to return in a single page.
pageToken (optional): A page token, received from a previous call, to retrieve the next page of results.

The tool gets the project and region from the source configuration.

dgraph-dql

Mon, 01 Jan 0001 00:00:00 +0000

Note

firebird-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A firebird-execute-sql tool executes a SQL statement against a Firebird database.

firebird-execute-sql takes one input parameter sql and runs the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Firebird

Example

kind: tool
name: execute_sql_tool
type: firebird-execute-sql
source: my_firebird_db
description: Use this tool to execute a SQL statement against the Firebird database.

Reference

field	type	required	description
type	string	true	Must be “firebird-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

firebird-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A firebird-sql tool executes a pre-defined SQL statement against a Firebird database.

The specified SQL statement is executed as a prepared statement, and supports both positional parameters (?) and named parameters (:param_name). Parameters will be inserted according to their position or name. If template parameters are included, they will be resolved before the execution of the prepared statement.

Compatible Sources

This tool can be used with the following database sources:

firestore-add-documents

Mon, 01 Jan 0001 00:00:00 +0000

About

The firestore-add-documents tool allows you to add new documents to a Firestore collection. It supports all Firestore data types using Firestore’s native JSON format. The tool automatically generates a unique document ID for each new document.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Firestore

Parameters

Parameter	Type	Required	Description
`collectionPath`	string	Yes	The path of the collection where the document will be added
`documentData`	map	Yes	The data to be added as a document to the given collection. Must use Firestore’s native JSON format with typed values
`returnData`	boolean	No	If set to true, the output will include the data of the created document. Defaults to false to help avoid overloading the context

Data Type Format

The tool requires Firestore’s native JSON format for document data. Each field must be wrapped with its type indicator:

firestore-delete-documents

Mon, 01 Jan 0001 00:00:00 +0000

About

A firestore-delete-documents tool deletes multiple documents from Firestore by their paths.

firestore-delete-documents takes one input parameter documentPaths which is an array of document paths to delete. The tool uses Firestore’s BulkWriter for efficient batch deletion and returns the success status for each document.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Firestore

Example

kind: tool
name: delete_user_documents
type: firestore-delete-documents
source: my-firestore-source
description: Use this tool to delete multiple documents from Firestore.

Reference

field	type	required	description
type	string	true	Must be “firestore-delete-documents”.
source	string	true	Name of the Firestore source to delete documents from.
description	string	true	Description of the tool that is passed to the LLM.

firestore-get-documents

Mon, 01 Jan 0001 00:00:00 +0000

About

A firestore-get-documents tool retrieves multiple documents from Firestore by their paths.

firestore-get-documents takes one input parameter documentPaths which is an array of document paths, and returns the documents’ data along with metadata such as existence status, creation time, update time, and read time.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Firestore

Example

kind: tool
name: get_user_documents
type: firestore-get-documents
source: my-firestore-source
description: Use this tool to retrieve multiple documents from Firestore.

Reference

field	type	required	description
type	string	true	Must be “firestore-get-documents”.
source	string	true	Name of the Firestore source to retrieve documents from.
description	string	true	Description of the tool that is passed to the LLM.

firestore-get-rules

Mon, 01 Jan 0001 00:00:00 +0000

About

A firestore-get-rules tool retrieves the active Firestore security rules for the current project.

firestore-get-rules takes no input parameters and returns the security rules content along with metadata such as the ruleset name, and timestamps.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Firestore

Example

kind: tool
name: get_firestore_rules
type: firestore-get-rules
source: my-firestore-source
description: Use this tool to retrieve the active Firestore security rules.

Reference

field	type	required	description
type	string	true	Must be “firestore-get-rules”.
source	string	true	Name of the Firestore source to retrieve rules from.
description	string	true	Description of the tool that is passed to the LLM.

firestore-list-collections

Mon, 01 Jan 0001 00:00:00 +0000

About

A firestore-list-collections tool lists collections in Firestore, either at the root level or as subcollections of a specific document.

firestore-list-collections takes an optional parentPath parameter to specify a document path. If provided, it lists all subcollections of that document. If not provided, it lists all root-level collections in the database.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Firestore

Example

kind: tool
name: list_firestore_collections
type: firestore-list-collections
source: my-firestore-source
description: Use this tool to list collections in Firestore.

Reference

field	type	required	description
type	string	true	Must be “firestore-list-collections”.
source	string	true	Name of the Firestore source to list collections from.
description	string	true	Description of the tool that is passed to the LLM.

firestore-query

Mon, 01 Jan 0001 00:00:00 +0000

About

The firestore-query tool allows you to query Firestore collections with dynamic, parameterizable filters that support Firestore’s native JSON value types. This tool is designed for querying single collection, which is the standard pattern in Firestore. The collection path itself can be parameterized, making it flexible for various use cases. This tool is particularly useful when you need to create reusable query templates with parameters that can be substituted at runtime.

firestore-query-collection

Mon, 01 Jan 0001 00:00:00 +0000

About

The firestore-query-collection tool allows you to query Firestore collections with filters, ordering, and limit capabilities.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Firestore

Parameters

parameters	type	required	default	description
`collectionPath`	string	true	-	The Firestore Rules source code to validate
`filters`	array	false	-	Array of filter objects (as JSON strings) to apply to the query
`orderBy`	string	false	-	JSON string specifying field and direction to order results
`limit`	integer	false	100	Maximum number of documents to return
`analyzeQuery`	boolean	false	false	If true, returns query explain metrics including execution statistics

Example

To use this tool, you need to configure it in your YAML configuration file:

firestore-update-document

Mon, 01 Jan 0001 00:00:00 +0000

About

The firestore-update-document tool allows you to update existing documents in Firestore. It supports all Firestore data types using Firestore’s native JSON format. The tool can perform both full document updates (replacing all fields) or selective field updates using an update mask. When using an update mask, fields referenced in the mask but not present in the document data will be deleted from the document, following Firestore’s native behavior.

Compatible Sources

This tool can be used with the following database sources:

firestore-validate-rules

Mon, 01 Jan 0001 00:00:00 +0000

About

The firestore-validate-rules tool validates Firestore security rules syntax and semantic correctness without deploying them. It provides detailed error reporting with source positions and code snippets.

Use Cases

Pre-deployment validation: Validate rules before deploying to production
CI/CD integration: Integrate rules validation into your build pipeline
Development workflow: Quickly check rules syntax while developing
Error debugging: Get detailed error locations with code snippets

Compatible Sources

This tool can be used with the following database sources:

Gemini Embedding

Mon, 01 Jan 0001 00:00:00 +0000

About

Google Gemini provides state-of-the-art embedding models that convert text into high-dimensional vectors.

Authentication

Toolbox uses your Application Default Credentials (ADC) to authorize with the Gemini API client.

Optionally, you can use an API key obtain an API Key from the Google AI Studio.

We recommend using an API key for testing and using application default credentials for production.

Behavior

Automatic Vectorization

When a tool parameter is configured with embeddedBy: <your-gemini-model-name>, the Toolbox intercepts the raw text input from the client and sends it to the Gemini API. The resulting numerical array is then formatted before being passed to your database source.

Google Sign-In

Mon, 01 Jan 0001 00:00:00 +0000

Getting Started

Google Sign-In manages the OAuth 2.0 flow and token lifecycle. To integrate the Google Sign-In workflow to your web app follow this guide.

After setting up the Google Sign-In workflow, you should have registered your application and retrieved a Client ID. Configure your auth service in with the Client ID.

Behavior

Authorized Invocations

When using Authorized Invocations, a tool will be considered authorized if it has a valid Oauth 2.0 token that matches the Client ID.

http

Mon, 01 Jan 0001 00:00:00 +0000

About

The http tool allows you to make HTTP requests to APIs to retrieve data. An HTTP request is the method by which a client communicates with a server to retrieve or manipulate resources. Toolbox allows you to configure the request URL, method, headers, query parameters, and the request body for an HTTP Tool.

Compatible Sources

This tool can be used with the following database sources:

Source Name
HTTP

URL

An HTTP request URL identifies the target the client wants to access. Toolbox composes the request URL from 3 places:

list_tables

Mon, 01 Jan 0001 00:00:00 +0000

About

An oracle-sql tool executes a pre-defined SQL statement against an Oracle database.

The specified SQL statement is executed using prepared statements for security and performance. It expects parameter placeholders in the SQL query to be in the native Oracle format (e.g., :1, :2).

By default, tools are configured as read-only (SAFE mode). To execute data modification statements (INSERT, UPDATE, DELETE), you must explicitly set the readOnly field to false.

Compatible Sources

This tool can be used with the following database sources:

looker-add-dashboard-element

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-add-dashboard-element tool creates a new tile (element) within an existing Looker dashboard. Tiles are added in the order this tool is called for a given dashboard_id.

CRITICAL ORDER OF OPERATIONS:

Create the dashboard using make_dashboard.
Add any dashboard-level filters using add_dashboard_filter.
Then, add elements (tiles) using this tool.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: add_dashboard_element
type: looker-add-dashboard-element
source: looker-source
description: |
 This tool creates a new tile (element) within an existing Looker dashboard.
 Tiles are added in the order this tool is called for a given `dashboard_id`.

 CRITICAL ORDER OF OPERATIONS:
 1. Create the dashboard using `make_dashboard`.
 2. Add any dashboard-level filters using `add_dashboard_filter`.
 3. Then, add elements (tiles) using this tool.

 Required Parameters:
 - dashboard_id: The ID of the target dashboard, obtained from `make_dashboard`.
 - model_name, explore_name, fields: These query parameters are inherited
 from the `query` tool and are required to define the data for the tile.

 Optional Parameters:
 - title: An optional title for the dashboard tile.
 - pivots, filters, sorts, limit, query_timezone: These query parameters are
 inherited from the `query` tool and can be used to customize the tile's query.
 - vis_config: A JSON object defining the visualization settings for this tile.
 The structure and options are the same as for the `query_url` tool's `vis_config`.

 Connecting to Dashboard Filters:
 A dashboard element can be connected to one or more dashboard filters (created with
 `add_dashboard_filter`). To do this, specify the `name` of the dashboard filter
 and the `field` from the element's query that the filter should apply to.
 The format for specifying the field is `view_name.field_name`.

Reference

field	type	required	description
type	string	true	Must be “looker-add-dashboard-element”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-add-dashboard-filter

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-add-dashboard-filter tool adds a filter to a specified Looker dashboard.

CRITICAL ORDER OF OPERATIONS:

Create a dashboard using make_dashboard.
Add all desired filters using this tool (add_dashboard_filter).
Finally, add dashboard elements (tiles) using add_dashboard_element.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Parameters

parameter	type	required	default	description
dashboard_id	string	true	none	The ID of the dashboard to add the filter to, obtained from `make_dashboard`.
name	string	true	none	A unique internal identifier for the filter. This name is used later in `add_dashboard_element` to bind tiles to this filter.
title	string	true	none	The label displayed to users in the Looker UI.
filter_type	string	true	`field_filter`	The filter type of filter. Can be `date_filter`, `number_filter`, `string_filter`, or `field_filter`.
default_value	string	false	none	The initial value for the filter.
model	string	if `field_filter`	none	The name of the LookML model, obtained from `get_models`.
explore	string	if `field_filter`	none	The name of the explore within the model, obtained from `get_explores`.
dimension	string	if `field_filter`	none	The name of the field (e.g., `view_name.field_name`) to base the filter on, obtained from `get_dimensions`.
allow_multiple_values	boolean	false	true	The Dashboard Filter should allow multiple values
required	boolean	false	false	The Dashboard Filter is required to run dashboard

Example

kind: tool
name: add_dashboard_filter
type: looker-add-dashboard-filter
source: looker-source
description: |
 This tool adds a filter to a Looker dashboard.

 CRITICAL ORDER OF OPERATIONS:
 1. Create a dashboard using `make_dashboard`.
 2. Add all desired filters using this tool (`add_dashboard_filter`).
 3. Finally, add dashboard elements (tiles) using `add_dashboard_element`.

 Parameters:
 - dashboard_id (required): The ID from `make_dashboard`.
 - name (required): A unique internal identifier for the filter. You will use this `name` later in `add_dashboard_element` to bind tiles to this filter.
 - title (required): The label displayed to users in the UI.
 - filter_type (required): One of `date_filter`, `number_filter`, `string_filter`, or `field_filter`.
 - default_value (optional): The initial value for the filter.

 Field Filters (`flter_type: field_filter`):
 If creating a field filter, you must also provide:
 - model
 - explore
 - dimension
 The filter will inherit suggestions and type information from this LookML field.

Reference

field	type	required	description
type	string	true	Must be “looker-add-dashboard-filter”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-conversational-analytics

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-conversational-analytics tool allows you to ask questions about your Looker data.

looker-conversational-analytics accepts two parameters:

user_query_with_context: The question asked of the Conversational Analytics system.
explore_references: A list of one to five explores that can be queried to answer the question. The form of the entry is [{"model": "model name", "explore": "explore name"}, ...]

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: ask_data_insights
type: looker-conversational-analytics
source: looker-source
description: |
 Use this tool to ask questions about your data using the Looker Conversational
 Analytics API. You must provide a natural language query and a list of
 1 to 5 model and explore combinations (e.g. [{'model': 'the_model', 'explore': 'the_explore'}]).
 Use the 'get_models' and 'get_explores' tools to discover available models and explores.

Reference

field	type	required	description
type	string	true	Must be “lookerca-conversational-analytics”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-create-project-directory

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-create-project-directory tool creates a new directory within a specified LookML project.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: looker-create-project-directory
type: looker-create-project-directory
source: looker-source
description: |
 This tool creates a new directory within a specific LookML project.
 It is useful for organizing project files.

 Parameters:
 - project_id (string): The ID of the LookML project.
 - directory_path (string): The path of the directory to create.

 Output:
 A string confirming the creation of the directory.

Reference

field	type	required	description
type	string	true	Must be “looker-create-project-directory”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-create-project-file

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-create-project-file tool creates a new LookML file in a project

looker-create-project-file accepts a project_id parameter and a file_path parameter as well as the file content.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: create_project_file
type: looker-create-project-file
source: looker-source
description: |
 This tool creates a new LookML file within a specified project, populating
 it with the provided content.

 Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.

 Parameters:
 - project_id (required): The unique ID of the LookML project.
 - file_path (required): The desired path and filename for the new file within the project.
 - content (required): The full LookML content to write into the new file.

 Output:
 A confirmation message upon successful file creation.

Reference

field	type	required	description
type	string	true	Must be “looker-create-project-file”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-delete-project-directory

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-delete-project-directory tool deletes a directory from a specified LookML project.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: looker-delete-project-directory
type: looker-delete-project-directory
source: looker-source
description: |
 This tool deletes a directory from a specific LookML project.
 It is useful for removing unnecessary or obsolete directories.

 Parameters:
 - project_id (string): The ID of the LookML project.
 - directory_path (string): The path of the directory to delete.

 Output:
 A string confirming the deletion of the directory.

Reference

field	type	required	description
type	string	true	Must be “looker-delete-project-directory”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-delete-project-file

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-delete-project-file tool deletes a LookML file in a project

looker-delete-project-file accepts a project_id parameter and a file_path parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: delete_project_file
type: looker-delete-project-file
source: looker-source
description: |
 This tool permanently deletes a specified LookML file from within a project.
 Use with caution, as this action cannot be undone through the API.

 Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.

 Parameters:
 - project_id (required): The unique ID of the LookML project.
 - file_path (required): The exact path to the LookML file to delete within the project.

 Output:
 A confirmation message upon successful file deletion.

Reference

field	type	required	description
type	string	true	Must be “looker-delete-project-file”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-dev-mode

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-dev-mode tool changes the session into and out of dev mode.

looker-dev-mode accepts a boolean parameter, true to enter dev mode and false to exit dev mode.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: dev_mode
type: looker-dev-mode
source: looker-source
description: |
 This tool allows toggling the Looker IDE session between Development Mode and Production Mode.
 Development Mode enables making and testing changes to LookML projects.

 Parameters:
 - enable (required): A boolean value.
 - `true`: Switches the current session to Development Mode.
 - `false`: Switches the current session to Production Mode.

Reference

field	type	required	description
type	string	true	Must be “looker-dev-mode”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-generate-embed-url

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-generate-embed-url tool generates an embeddable URL for a given piece of Looker content. The url generated is created for the user authenticated to the Looker source. When opened in the browser it will create a Looker Embed session.

looker-generate-embed-url takes two parameters:

the type of content (e.g., “dashboards”, “looks”, “query-visualization”)
the id of the content

It’s recommended to use other tools from the Looker MCP toolbox with this tool to do things like fetch dashboard id’s, generate a query, etc that can be supplied to this tool.

looker-get-connection-databases

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-connection-databases tool returns all the databases in a connection.

looker-get-connection-databases accepts a conn parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_connection_databases
type: looker-get-connection-databases
source: looker-source
description: |
 This tool retrieves a list of databases available through a specified Looker connection.
 This is only applicable for connections that support multiple databases.
 Use `get_connections` to check if a connection supports multiple databases.

 Parameters:
 - connection_name (required): The name of the database connection, obtained from `get_connections`.

 Output:
 A JSON array of strings, where each string is the name of an available database.
 If the connection does not support multiple databases, an empty list or an error will be returned.

Reference

field	type	required	description
type	string	true	Must be “looker-get-connection-databases”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-connection-schemas

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-connection-schemas tool returns all the schemas in a connection.

looker-get-connection-schemas accepts a conn parameter and an optional db parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_connection_schemas
type: looker-get-connection-schemas
source: looker-source
description: |
 This tool retrieves a list of database schemas available through a specified
 Looker connection.

 Parameters:
 - connection_name (required): The name of the database connection, obtained from `get_connections`.
 - database (optional): An optional database name to filter the schemas.
 Only applicable for connections that support multiple databases.

 Output:
 A JSON array of strings, where each string is the name of an available schema.

Reference

field	type	required	description
type	string	true	Must be “looker-get-connection-schemas”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-connection-table-columns

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-connection-table-columns tool returns all the columnes for each table specified.

looker-get-connection-table-columns accepts a conn parameter, a schema parameter, a tables parameter with a comma separated list of tables, and an optional db parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_connection_table_columns
type: looker-get-connection-table-columns
source: looker-source
description: |
 This tool retrieves a list of columns for one or more specified tables within a
 given database schema and connection.

 Parameters:
 - connection_name (required): The name of the database connection, obtained from `get_connections`.
 - schema (required): The name of the schema where the tables reside, obtained from `get_connection_schemas`.
 - tables (required): A comma-separated string of table names for which to retrieve columns
 (e.g., "users,orders,products"), obtained from `get_connection_tables`.
 - database (optional): The name of the database to filter by. Only applicable for connections
 that support multiple databases (check with `get_connections`).

 Output:
 A JSON array of objects, where each object represents a column and contains details
 such as `table_name`, `column_name`, `data_type`, and `is_nullable`.

Reference

field	type	required	description
type	string	true	Must be “looker-get-connection-table-columns”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-connection-tables

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-connection-tables tool returns all the tables in a connection.

looker-get-connection-tables accepts a conn parameter, a schema parameter, and an optional db parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_connection_tables
type: looker-get-connection-tables
source: looker-source
description: |
 This tool retrieves a list of tables available within a specified database schema
 through a Looker connection.

 Parameters:
 - connection_name (required): The name of the database connection, obtained from `get_connections`.
 - schema (required): The name of the schema to list tables from, obtained from `get_connection_schemas`.
 - database (optional): The name of the database to filter by. Only applicable for connections
 that support multiple databases (check with `get_connections`).

 Output:
 A JSON array of strings, where each string is the name of an available table.

Reference

field	type	required	description
type	string	true	Must be “looker-get-connection-tables”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-connections

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-connections tool returns all the connections in the source.

looker-get-connections accepts no parameters.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_connections
type: looker-get-connections
source: looker-source
description: |
 This tool retrieves a list of all database connections configured in the Looker system.

 Parameters:
 This tool takes no parameters.

 Output:
 A JSON array of objects, each representing a database connection and including details such as:
 - `name`: The connection's unique identifier.
 - `dialect`: The database dialect (e.g., "mysql", "postgresql", "bigquery").
 - `default_schema`: The default schema for the connection.
 - `database`: The associated database name (if applicable).
 - `supports_multiple_databases`: A boolean indicating if the connection can access multiple databases.

Reference

field	type	required	description
type	string	true	Must be “looker-get-connections”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-dashboards

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-get-dashboards tool searches for a saved Dashboard by name or description.

looker-get-dashboards takes four parameters, the title, desc, limit and offset.

Title and description use SQL style wildcards and are case insensitive.

Limit and offset are used to page through a larger set of matches and default to 100 and 0.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_dashboards
type: looker-get-dashboards
source: looker-source
description: |
 This tool searches for saved dashboards in a Looker instance. It returns a list of JSON objects, each representing a dashboard.

 Search Parameters:
 - title (optional): Filter by dashboard title (supports wildcards).
 - folder_id (optional): Filter by the ID of the folder where the dashboard is saved.
 - user_id (optional): Filter by the ID of the user who created the dashboard.
 - description (optional): Filter by description content (supports wildcards).
 - id (optional): Filter by specific dashboard ID.
 - limit (optional): Maximum number of results to return. Defaults to a system limit.
 - offset (optional): Starting point for pagination.

 String Search Behavior:
 - Case-insensitive matching.
 - Supports SQL LIKE pattern match wildcards:
 - `%`: Matches any sequence of zero or more characters. (e.g., `"finan%"` matches "financial", "finance")
 - `_`: Matches any single character. (e.g., `"s_les"` matches "sales")
 - Special expressions for null checks:
 - `"IS NULL"`: Matches dashboards where the field is null.
 - `"NOT NULL"`: Excludes dashboards where the field is null.

Reference

field	type	required	description
type	string	true	Must be “looker-get-dashboards”
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-dimensions

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-dimensions tool returns all the dimensions from a given explore in a given model in the source.

looker-get-dimensions accepts two parameters, the model and the explore.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_dimensions
type: looker-get-dimensions
source: looker-source
description: |
 This tool retrieves a list of dimensions defined within a specific Looker explore.
 Dimensions are non-aggregatable attributes or characteristics of your data
 (e.g., product name, order date, customer city) that can be used for grouping,
 filtering, or segmenting query results.

 Parameters:
 - model_name (required): The name of the LookML model, obtained from `get_models`.
 - explore_name (required): The name of the explore within the model, obtained from `get_explores`.

 Output Details:
 - If a dimension includes a `suggestions` field, its contents are valid values
 that can be used directly as filters for that dimension.
 - If a `suggest_explore` and `suggest_dimension` are provided, you can query
 that specified explore and dimension to retrieve a list of valid filter values.

The response is a json array with the following elements:

looker-get-explores

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-explores tool returns all explores for a given model from the source.

looker-get-explores accepts one parameter, the model id.

The return type is an array of maps, each map is formatted like:

{
 "name": "explore name",
 "description": "explore description",
 "label": "explore label",
 "group_label": "group label"
}

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_explores
type: looker-get-explores
source: looker-source
description: |
 This tool retrieves a list of explores defined within a specific LookML model.
 Explores represent a curated view of your data, typically joining several
 tables together to allow for focused analysis on a particular subject area.
 The output provides details like the explore's `name` and `label`.

 Parameters:
 - model_name (required): The name of the LookML model, obtained from `get_models`.

Reference

field	type	required	description
type	string	true	Must be “looker-get-explores”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-filters

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-filters tool returns all the filters from a given explore in a given model in the source.

looker-get-filters accepts two parameters, the model and the explore.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_filters
type: looker-get-filters
source: looker-source
description: |
 This tool retrieves a list of "filter-only fields" defined within a specific
 Looker explore. These are special fields defined in LookML specifically to
 create user-facing filter controls that do not directly affect the `GROUP BY`
 clause of the SQL query. They are often used in conjunction with liquid templating
 to create dynamic queries.

 Note: Regular dimensions and measures can also be used as filters in a query.
 This tool *only* returns fields explicitly defined as `filter:` in LookML.

 Parameters:
 - model_name (required): The name of the LookML model, obtained from `get_models`.
 - explore_name (required): The name of the explore within the model, obtained from `get_explores`.

The response is a json array with the following elements:

looker-get-looks

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-get-looks tool searches for a saved Look by name or description.

looker-get-looks takes four parameters, the title, desc, limit and offset.

Title and description use SQL style wildcards and are case insensitive.

Limit and offset are used to page through a larger set of matches and default to 100 and 0.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_looks
type: looker-get-looks
source: looker-source
description: |
 This tool searches for saved Looks (pre-defined queries and visualizations)
 in a Looker instance. It returns a list of JSON objects, each representing a Look.

 Search Parameters:
 - title (optional): Filter by Look title (supports wildcards).
 - folder_id (optional): Filter by the ID of the folder where the Look is saved.
 - user_id (optional): Filter by the ID of the user who created the Look.
 - description (optional): Filter by description content (supports wildcards).
 - id (optional): Filter by specific Look ID.
 - limit (optional): Maximum number of results to return. Defaults to a system limit.
 - offset (optional): Starting point for pagination.

 String Search Behavior:
 - Case-insensitive matching.
 - Supports SQL LIKE pattern match wildcards:
 - `%`: Matches any sequence of zero or more characters. (e.g., `"dan%"` matches "danger", "Danzig")
 - `_`: Matches any single character. (e.g., `"D_m%"` matches "Damage", "dump")
 - Special expressions for null checks:
 - `"IS NULL"`: Matches Looks where the field is null.
 - `"NOT NULL"`: Excludes Looks where the field is null.

Reference

field	type	required	description
type	string	true	Must be “looker-get-looks”
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-measures

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-measures tool returns all the measures from a given explore in a given model in the source.

looker-get-measures accepts two parameters, the model and the explore.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_measures
type: looker-get-measures
source: looker-source
description: |
 This tool retrieves a list of measures defined within a specific Looker explore.
 Measures are aggregatable metrics (e.g., total sales, average price, count of users)
 that are used for calculations and quantitative analysis in your queries.

 Parameters:
 - model_name (required): The name of the LookML model, obtained from `get_models`.
 - explore_name (required): The name of the explore within the model, obtained from `get_explores`.

 Output Details:
 - If a measure includes a `suggestions` field, its contents are valid values
 that can be used directly as filters for that measure.
 - If a `suggest_explore` and `suggest_dimension` are provided, you can query
 that specified explore and dimension to retrieve a list of valid filter values.

The response is a json array with the following elements:

looker-get-models

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-models tool returns all the models in the source.

looker-get-models accepts no parameters.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_models
type: looker-get-models
source: looker-source
description: |
 This tool retrieves a list of available LookML models in the Looker instance.
 LookML models define the data structure and relationships that users can query.
 The output includes details like the model's `name` and `label`, which are
 essential for subsequent calls to tools like `get_explores` or `query`.

 This tool takes no parameters.

Reference

field	type	required	description
type	string	true	Must be “looker-get-models”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-parameters

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-parameters tool returns all the parameters from a given explore in a given model in the source.

looker-get-parameters accepts two parameters, the model and the explore.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_parameters
type: looker-get-parameters
source: looker-source
description: |
 This tool retrieves a list of parameters defined within a specific Looker explore.
 LookML parameters are dynamic input fields that allow users to influence query
 behavior without directly modifying the underlying LookML. They are often used
 with `liquid` templating to create flexible dashboards and reports, enabling
 users to choose dimensions, measures, or other query components at runtime.

 Parameters:
 - model_name (required): The name of the LookML model, obtained from `get_models`.
 - explore_name (required): The name of the explore within the model, obtained from `get_explores`.

The response is a json array with the following elements:

looker-get-project-directories

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-project-directories tool retrieves the directories within a specified LookML project.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: looker-get-project-directories
type: looker-get-project-directories
source: looker-source
description: |
 This tool retrieves a list of directories within a specific LookML project.
 It is useful for exploring the project structure.

 Parameters:
 - project_id (string): The ID of the LookML project.

 Output:
 A JSON array of strings, representing the directories within the project.

Reference

field	type	required	description
type	string	true	Must be “looker-get-project-directories”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-project-file

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-project-file tool returns the contents of a LookML file.

looker-get-project-file accepts a project_id parameter and a file_path parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_project_file
type: looker-get-project-file
source: looker-source
description: |
 This tool retrieves the raw content of a specific LookML file from within a project.

 Parameters:
 - project_id (required): The unique ID of the LookML project, obtained from `get_projects`.
 - file_path (required): The path to the LookML file within the project,
 typically obtained from `get_project_files`.

 Output:
 The raw text content of the specified LookML file.

Reference

field	type	required	description
type	string	true	Must be “looker-get-project-file”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-project-files

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-project-files tool returns all the lookml files in a project in the source.

looker-get-project-files accepts a project_id parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_project_files
type: looker-get-project-files
source: looker-source
description: |
 This tool retrieves a list of all LookML files within a specified project,
 providing details about each file.

 Parameters:
 - project_id (required): The unique ID of the LookML project, obtained from `get_projects`.

 Output:
 A JSON array of objects, each representing a LookML file and containing
 details such as `path`, `id`, `type`, and `git_status`.

Reference

field	type	required	description
type	string	true	Must be “looker-get-project-files”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-get-projects

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-get-projects tool returns all the projects in the source.

looker-get-projects accepts no parameters.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: get_projects
type: looker-get-projects
source: looker-source
description: |
 This tool retrieves a list of all LookML projects available on the Looker instance.
 It is useful for identifying projects before performing actions like retrieving
 project files or making modifications.

 Parameters:
 This tool takes no parameters.

 Output:
 A JSON array of objects, each containing the `project_id` and `project_name`
 for a LookML project.

Reference

field	type	required	description
type	string	true	Must be “looker-get-projects”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-git-branch

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-git-branch tool is used to retrieve and manipulate the git branch of a LookML project.

looker-git-branch requires two parameters, the LookML project_id and the operation. The operation must be one of list, get, create, switch, or delete.

The list operation retrieves the list of available branches. The get operation retrieves the current branch.

create, switch and delete all require an additional parameter, the branch name. The create operation creates a new branch. The switch operation switches to the specified branch. The delete operation deletes the specified branch.

looker-health-analyze

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-health-analyze tool performs various analysis tasks on a Looker instance. The action parameter selects the type of analysis to perform:

projects: Analyzes all projects or a specified project, reporting on the number of models and view files, as well as Git connection and validation status.
models: Analyzes all models or a specified model, providing a count of explores, unused explores, and total query counts.
explores: Analyzes all explores or a specified explore, reporting on the number of joins, unused joins, fields, unused fields, and query counts. Being classified as Unused is determined by whether a field has been used as a field or filter within the past 90 days in production.

Compatible Sources

This tool can be used with the following database sources:

looker-health-pulse

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-health-pulse tool performs health checks on a Looker instance. The action parameter selects the type of check to perform:

check_db_connections: Checks all database connections, runs supported tests, and reports query counts.
check_dashboard_performance: Finds dashboards with slow running queries in the last 7 days.
check_dashboard_errors: Lists dashboards with erroring queries in the last 7 days.
check_explore_performance: Lists the slowest explores in the last 7 days and reports average query runtime.
check_schedule_failures: Lists schedules that have failed in the last 7 days.
check_legacy_features: Lists enabled legacy features. (To note, this function is not available in Looker Core.)

Compatible Sources

This tool can be used with the following database sources:

looker-health-vacuum

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-health-vacuum tool helps you identify unused LookML objects such as models, explores, joins, and fields. The action parameter selects the type of vacuum to perform:

models: Identifies unused explores within a model.
explores: Identifies unused joins and fields within an explore.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Parameters

field	type	required	description
action	string	true	The vacuum to perform: `models`, or `explores`.
project	string	false	The name of the Looker project to vacuum.
model	string	false	The name of the Looker model to vacuum.
explore	string	false	The name of the Looker explore to vacuum.
timeframe	int	false	The timeframe in days to analyze for usage. Defaults to 90.
min_queries	int	false	The minimum number of queries for an object to be considered used. Defaults to 1.

Example

Identify unnused fields (in this case, less than 1 query in the last 20 days) and joins in the order_items explore and thelook model

looker-make-dashboard

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-make-dashboard creates a dashboard in the user’s Looker personal folder.

looker-make-dashboard takes three parameters:

the title
the description
an optional folder id. If not provided, the user’s default folder will be used.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: make_dashboard
type: looker-make-dashboard
source: looker-source
description: |
 This tool creates a new, empty dashboard in Looker. Dashboards are stored
 in the user's personal folder, and the dashboard name must be unique.
 After creation, use `add_dashboard_filter` to add filters and
 `add_dashboard_element` to add content tiles.

 Required Parameters:
 - title (required): A unique title for the new dashboard.
 - description (required): A brief description of the dashboard's purpose.

 Output:
 A JSON object containing a link (`url`) to the newly created dashboard and
 its unique `id`. This `dashboard_id` is crucial for subsequent calls to
 `add_dashboard_filter` and `add_dashboard_element`.

Reference

field	type	required	description
type	string	true	Must be “looker-make-dashboard”
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-make-look

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-make-look creates a saved Look in the user’s Looker personal folder.

looker-make-look takes twelve parameters:

the model
the explore
the fields list
an optional set of filters
an optional set of pivots
an optional set of sorts
an optional limit
an optional tz
an optional vis_config
the title
an optional description
an optional folder id. If not provided, the user’s default folder will be used.

Compatible Sources

This tool can be used with the following database sources:

looker-query

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-query tool runs a query using the Looker semantic model.

looker-query takes eight parameters:

the model
the explore
the fields list
an optional set of filters
an optional set of pivots
an optional set of sorts
an optional limit
an optional tz

Starting in Looker v25.18, these queries can be identified in Looker’s System Activity. In the History explore, use the field API Client Name to find MCP Toolbox queries.

looker-query-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-query-sql generates a sql query using the Looker semantic model.

looker-query-sql takes eight parameters:

the model
the explore
the fields list
an optional set of filters
an optional set of pivots
an optional set of sorts
an optional limit
an optional tz

Starting in Looker v25.18, these queries can be identified in Looker’s System Activity. In the History explore, use the field API Client Name to find MCP Toolbox queries.

looker-query-url

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-query-url generates a url link to an explore in Looker so the query can be investigated further.

looker-query-url takes nine parameters:

the model
the explore
the fields list
an optional set of filters
an optional set of pivots
an optional set of sorts
an optional limit
an optional tz
an optional vis_config

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: query_url
type: looker-query-url
source: looker-source
description: |
 This tool generates a shareable URL for a Looker query, allowing users to
 explore the query further within the Looker UI. It returns the generated URL,
 along with the `query_id` and `slug`.

 Parameters:
 All query parameters (e.g., `model_name`, `explore_name`, `fields`, `pivots`,
 `filters`, `sorts`, `limit`, `query_timezone`) are the same as the `query` tool.

 Additionally, it accepts an optional `vis_config` parameter:
 - vis_config (optional): A JSON object that controls the default visualization
 settings for the generated query.

 vis_config Details:
 The `vis_config` object supports a wide range of properties for various chart types.
 Here are some notes on making visualizations.

 ### Cartesian Charts (Area, Bar, Column, Line, Scatter)

 These chart types share a large number of configuration options.

 **General**
 * `type`: The type of visualization (`looker_area`, `looker_bar`, `looker_column`, `looker_line`, `looker_scatter`).
 * `series_types`: Override the chart type for individual series.
 * `show_view_names`: Display view names in labels and tooltips (`true`/`false`).
 * `series_labels`: Provide custom names for series.

 **Styling & Colors**
 * `colors`: An array of color values to be used for the chart series.
 * `series_colors`: A mapping of series names to specific color values.
 * `color_application`: Advanced controls for color palette application (collection, palette, reverse, etc.).
 * `font_size`: Font size for labels (e.g., '12px').

 **Legend**
 * `hide_legend`: Show or hide the chart legend (`true`/`false`).
 * `legend_position`: Placement of the legend (`'center'`, `'left'`, `'right'`).

 **Axes**
 * `swap_axes`: Swap the X and Y axes (`true`/`false`).
 * `x_axis_scale`: Scale of the x-axis (`'auto'`, `'ordinal'`, `'linear'`, `'time'`).
 * `x_axis_reversed`, `y_axis_reversed`: Reverse the direction of an axis (`true`/`false`).
 * `x_axis_gridlines`, `y_axis_gridlines`: Display gridlines for an axis (`true`/`false`).
 * `show_x_axis_label`, `show_y_axis_label`: Show or hide the axis title (`true`/`false`).
 * `show_x_axis_ticks`, `show_y_axis_ticks`: Show or hide axis tick marks (`true`/`false`).
 * `x_axis_label`, `y_axis_label`: Set a custom title for an axis.
 * `x_axis_datetime_label`: A format string for datetime labels on the x-axis (e.g., `'%Y-%m'`).
 * `x_padding_left`, `x_padding_right`: Adjust padding on the ends of the x-axis.
 * `x_axis_label_rotation`, `x_axis_label_rotation_bar`: Set rotation for x-axis labels.
 * `x_axis_zoom`, `y_axis_zoom`: Enable zooming on an axis (`true`/`false`).
 * `y_axes`: An array of configuration objects for multiple y-axes.

 **Data & Series**
 * `stacking`: How to stack series (`''` for none, `'normal'`, `'percent'`).
 * `ordering`: Order of series in a stack (`'none'`, etc.).
 * `limit_displayed_rows`: Enable or disable limiting the number of rows displayed (`true`/`false`).
 * `limit_displayed_rows_values`: Configuration for the row limit (e.g., `{ "first_last": "first", "show_hide": "show", "num_rows": 10 }`).
 * `discontinuous_nulls`: How to render null values in line charts (`true`/`false`).
 * `point_style`: Style for points on line and area charts (`'none'`, `'circle'`, `'circle_outline'`).
 * `series_point_styles`: Override point styles for individual series.
 * `interpolation`: Line interpolation style (`'linear'`, `'monotone'`, `'step'`, etc.).
 * `show_value_labels`: Display values on data points (`true`/`false`).
 * `label_value_format`: A format string for value labels.
 * `show_totals_labels`: Display total labels on stacked charts (`true`/`false`).
 * `totals_color`: Color for total labels.
 * `show_silhouette`: Display a "silhouette" of hidden series in stacked charts (`true`/`false`).
 * `hidden_series`: An array of series names to hide from the visualization.

 **Scatter/Bubble Specific**
 * `size_by_field`: The field used to determine the size of bubbles.
 * `color_by_field`: The field used to determine the color of bubbles.
 * `plot_size_by_field`: Whether to display the size-by field in the legend.
 * `cluster_points`: Group nearby points into clusters (`true`/`false`).
 * `quadrants_enabled`: Display quadrants on the chart (`true`/`false`).
 * `quadrant_properties`: Configuration for quadrant labels and colors.
 * `custom_quadrant_value_x`, `custom_quadrant_value_y`: Set quadrant boundaries as a percentage.
 * `custom_quadrant_point_x`, `custom_quadrant_point_y`: Set quadrant boundaries to a specific value.

 **Miscellaneous**
 * `reference_lines`: Configuration for displaying reference lines.
 * `trend_lines`: Configuration for displaying trend lines.
 * `trellis`: Configuration for creating trellis (small multiple) charts.
 * `crossfilterEnabled`, `crossfilters`: Configuration for cross-filtering interactions.

 ### Boxplot

 * Inherits most of the Cartesian chart options.
 * `type`: Must be `looker_boxplot`.

 ### Funnel

 * `type`: Must be `looker_funnel`.
 * `orientation`: How data is read (`'automatic'`, `'dataInRows'`, `'dataInColumns'`).
 * `percentType`: How percentages are calculated (`'percentOfMaxValue'`, `'percentOfPriorRow'`).
 * `labelPosition`, `valuePosition`, `percentPosition`: Placement of labels (`'left'`, `'right'`, `'inline'`, `'hidden'`).
 * `labelColor`, `labelColorEnabled`: Set a custom color for labels.
 * `labelOverlap`: Allow labels to overlap (`true`/`false`).
 * `barColors`: An array of colors for the funnel steps.
 * `color_application`: Advanced color palette controls.
 * `crossfilterEnabled`, `crossfilters`: Configuration for cross-filtering.

 ### Pie / Donut

 * `type`: Must be `looker_pie`.
 * `value_labels`: Where to display values (`'legend'`, `'labels'`).
 * `label_type`: The format of data labels (`'labPer'`, `'labVal'`, `'lab'`, `'val'`, `'per'`).
 * `start_angle`, `end_angle`: The start and end angles of the pie chart.
 * `inner_radius`: The inner radius, used to create a donut chart.
 * `series_colors`, `series_labels`: Override colors and labels for specific slices.
 * `color_application`: Advanced color palette controls.
 * `crossfilterEnabled`, `crossfilters`: Configuration for cross-filtering.
 * `advanced_vis_config`: A string containing JSON for advanced Highcharts configuration.

 ### Waterfall

 * Inherits most of the Cartesian chart options.
 * `type`: Must be `looker_waterfall`.
 * `up_color`: Color for positive (increasing) values.
 * `down_color`: Color for negative (decreasing) values.
 * `total_color`: Color for the total bar.

 ### Word Cloud

 * `type`: Must be `looker_wordcloud`.
 * `rotation`: Enable random word rotation (`true`/`false`).
 * `colors`: An array of colors for the words.
 * `color_application`: Advanced color palette controls.
 * `crossfilterEnabled`, `crossfilters`: Configuration for cross-filtering.

 These are some sample vis_config settings.

 A bar chart -
 {{
 "defaults_version": 1,
 "label_density": 25,
 "legend_position": "center",
 "limit_displayed_rows": false,
 "ordering": "none",
 "plot_size_by_field": false,
 "point_style": "none",
 "show_null_labels": false,
 "show_silhouette": false,
 "show_totals_labels": false,
 "show_value_labels": false,
 "show_view_names": false,
 "show_x_axis_label": true,
 "show_x_axis_ticks": true,
 "show_y_axis_labels": true,
 "show_y_axis_ticks": true,
 "stacking": "normal",
 "totals_color": "#808080",
 "trellis": "",
 "type": "looker_bar",
 "x_axis_gridlines": false,
 "x_axis_reversed": false,
 "x_axis_scale": "auto",
 "x_axis_zoom": true,
 "y_axis_combined": true,
 "y_axis_gridlines": true,
 "y_axis_reversed": false,
 "y_axis_scale_mode": "linear",
 "y_axis_tick_density": "default",
 "y_axis_tick_density_custom": 5,
 "y_axis_zoom": true
 }}

 A column chart with an option advanced_vis_config -
 {{
 "advanced_vis_config": "{ chart: { type: 'pie', spacingBottom: 50, spacingLeft: 50, spacingRight: 50, spacingTop: 50, }, legend: { enabled: false, }, plotOptions: { pie: { dataLabels: { enabled: true, format: '\u003cb\u003e{key}\u003c/b\u003e\u003cspan style=\"font-weight: normal\"\u003e - {percentage:.2f}%\u003c/span\u003e', }, showInLegend: false, }, }, series: [], }",
 "colors": [
 "grey"
 ],
 "defaults_version": 1,
 "hidden_fields": [],
 "label_density": 25,
 "legend_position": "center",
 "limit_displayed_rows": false,
 "note_display": "below",
 "note_state": "collapsed",
 "note_text": "Unsold inventory only",
 "ordering": "none",
 "plot_size_by_field": false,
 "point_style": "none",
 "series_colors": {},
 "show_null_labels": false,
 "show_silhouette": false,
 "show_totals_labels": false,
 "show_value_labels": true,
 "show_view_names": false,
 "show_x_axis_label": true,
 "show_x_axis_ticks": true,
 "show_y_axis_labels": true,
 "show_y_axis_ticks": true,
 "stacking": "normal",
 "totals_color": "#808080",
 "trellis": "",
 "type": "looker_column",
 "x_axis_gridlines": false,
 "x_axis_reversed": false,
 "x_axis_scale": "auto",
 "x_axis_zoom": true,
 "y_axes": [],
 "y_axis_combined": true,
 "y_axis_gridlines": true,
 "y_axis_reversed": false,
 "y_axis_scale_mode": "linear",
 "y_axis_tick_density": "default",
 "y_axis_tick_density_custom": 5,
 "y_axis_zoom": true
 }}

 A line chart -
 {{
 "defaults_version": 1,
 "hidden_pivots": {},
 "hidden_series": [],
 "interpolation": "linear",
 "label_density": 25,
 "legend_position": "center",
 "limit_displayed_rows": false,
 "plot_size_by_field": false,
 "point_style": "none",
 "series_types": {},
 "show_null_points": true,
 "show_value_labels": false,
 "show_view_names": false,
 "show_x_axis_label": true,
 "show_x_axis_ticks": true,
 "show_y_axis_labels": true,
 "show_y_axis_ticks": true,
 "stacking": "",
 "trellis": "",
 "type": "looker_line",
 "x_axis_gridlines": false,
 "x_axis_reversed": false,
 "x_axis_scale": "auto",
 "y_axis_combined": true,
 "y_axis_gridlines": true,
 "y_axis_reversed": false,
 "y_axis_scale_mode": "linear",
 "y_axis_tick_density": "default",
 "y_axis_tick_density_custom": 5
 }}

 An area chart -
 {{
 "defaults_version": 1,
 "interpolation": "linear",
 "label_density": 25,
 "legend_position": "center",
 "limit_displayed_rows": false,
 "plot_size_by_field": false,
 "point_style": "none",
 "series_types": {},
 "show_null_points": true,
 "show_silhouette": false,
 "show_totals_labels": false,
 "show_value_labels": false,
 "show_view_names": false,
 "show_x_axis_label": true,
 "show_x_axis_ticks": true,
 "show_y_axis_labels": true,
 "show_y_axis_ticks": true,
 "stacking": "normal",
 "totals_color": "#808080",
 "trellis": "",
 "type": "looker_area",
 "x_axis_gridlines": false,
 "x_axis_reversed": false,
 "x_axis_scale": "auto",
 "x_axis_zoom": true,
 "y_axis_combined": true,
 "y_axis_gridlines": true,
 "y_axis_reversed": false,
 "y_axis_scale_mode": "linear",
 "y_axis_tick_density": "default",
 "y_axis_tick_density_custom": 5,
 "y_axis_zoom": true
 }}

 A scatter plot -
 {{
 "cluster_points": false,
 "custom_quadrant_point_x": 5,
 "custom_quadrant_point_y": 5,
 "custom_value_label_column": "",
 "custom_x_column": "",
 "custom_y_column": "",
 "defaults_version": 1,
 "hidden_fields": [],
 "hidden_pivots": {},
 "hidden_points_if_no": [],
 "hidden_series": [],
 "interpolation": "linear",
 "label_density": 25,
 "legend_position": "center",
 "limit_displayed_rows": false,
 "limit_displayed_rows_values": {
 "first_last": "first",
 "num_rows": 0,
 "show_hide": "hide"
 },
 "plot_size_by_field": false,
 "point_style": "circle",
 "quadrant_properties": {
 "0": {
 "color": "",
 "label": "Quadrant 1"
 },
 "1": {
 "color": "",
 "label": "Quadrant 2"
 },
 "2": {
 "color": "",
 "label": "Quadrant 3"
 },
 "3": {
 "color": "",
 "label": "Quadrant 4"
 }
 },
 "quadrants_enabled": false,
 "series_labels": {},
 "series_types": {},
 "show_null_points": false,
 "show_value_labels": false,
 "show_view_names": true,
 "show_x_axis_label": true,
 "show_x_axis_ticks": true,
 "show_y_axis_labels": true,
 "show_y_axis_ticks": true,
 "size_by_field": "roi",
 "stacking": "normal",
 "swap_axes": true,
 "trellis": "",
 "type": "looker_scatter",
 "x_axis_gridlines": false,
 "x_axis_reversed": false,
 "x_axis_scale": "auto",
 "x_axis_zoom": true,
 "y_axes": [
 {
 "label": "",
 "orientation": "bottom",
 "series": [
 {
 "axisId": "Channel_0 - average_of_roi_first",
 "id": "Channel_0 - average_of_roi_first",
 "name": "Channel_0"
 },
 {
 "axisId": "Channel_1 - average_of_roi_first",
 "id": "Channel_1 - average_of_roi_first",
 "name": "Channel_1"
 },
 {
 "axisId": "Channel_2 - average_of_roi_first",
 "id": "Channel_2 - average_of_roi_first",
 "name": "Channel_2"
 },
 {
 "axisId": "Channel_3 - average_of_roi_first",
 "id": "Channel_3 - average_of_roi_first",
 "name": "Channel_3"
 },
 {
 "axisId": "Channel_4 - average_of_roi_first",
 "id": "Channel_4 - average_of_roi_first",
 "name": "Channel_4"
 }
 ],
 "showLabels": true,
 "showValues": true,
 "tickDensity": "custom",
 "tickDensityCustom": 100,
 "type": "linear",
 "unpinAxis": false
 }
 ],
 "y_axis_combined": true,
 "y_axis_gridlines": true,
 "y_axis_reversed": false,
 "y_axis_scale_mode": "linear",
 "y_axis_tick_density": "default",
 "y_axis_tick_density_custom": 5,
 "y_axis_zoom": true
 }}

 A single record visualization -
 {{
 "defaults_version": 1,
 "show_view_names": false,
 "type": "looker_single_record"
 }}

 A single value visualization -
 {{
 "comparison_reverse_colors": false,
 "comparison_type": "value", "conditional_formatting_include_nulls": false, "conditional_formatting_include_totals": false,
 "custom_color": "#1A73E8",
 "custom_color_enabled": true,
 "defaults_version": 1,
 "enable_conditional_formatting": false,
 "series_types": {},
 "show_comparison": false,
 "show_comparison_label": true,
 "show_single_value_title": true,
 "single_value_title": "Total Clicks",
 "type": "single_value"
 }}

 A Pie chart -
 {{
 "defaults_version": 1,
 "label_density": 25,
 "label_type": "labPer",
 "legend_position": "center",
 "limit_displayed_rows": false,
 "ordering": "none",
 "plot_size_by_field": false,
 "point_style": "none",
 "series_types": {},
 "show_null_labels": false,
 "show_silhouette": false,
 "show_totals_labels": false,
 "show_value_labels": false,
 "show_view_names": false,
 "show_x_axis_label": true,
 "show_x_axis_ticks": true,
 "show_y_axis_labels": true,
 "show_y_axis_ticks": true,
 "stacking": "",
 "totals_color": "#808080",
 "trellis": "",
 "type": "looker_pie",
 "value_labels": "legend",
 "x_axis_gridlines": false,
 "x_axis_reversed": false,
 "x_axis_scale": "auto",
 "y_axis_combined": true,
 "y_axis_gridlines": true,
 "y_axis_reversed": false,
 "y_axis_scale_mode": "linear",
 "y_axis_tick_density": "default",
 "y_axis_tick_density_custom": 5
 }}

 The result is a JSON object with the id, slug, the url, and
 the long_url.

Reference

field	type	required	description
type	string	true	Must be “looker-query-url”
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-run-dashboard

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-run-dashboard tool runs the queries associated with a dashboard.

looker-run-dashboard takes one parameter, the dashboard_id.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: run_dashboard
type: looker-run-dashboard
source: looker-source
description: |
 This tool executes the queries associated with each tile in a specified dashboard
 and returns the aggregated data in a JSON structure.

 Parameters:
 - dashboard_id (required): The unique identifier of the dashboard to run,
 typically obtained from the `get_dashboards` tool.

 Output:
 The data from all dashboard tiles is returned as a JSON object.

Reference

field	type	required	description
type	string	true	Must be “looker-run-dashboard”
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-run-look

Mon, 01 Jan 0001 00:00:00 +0000

About

The looker-run-look tool runs the query associated with a saved Look.

looker-run-look takes one parameter, the look_id.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: run_look
type: looker-run-look
source: looker-source
description: |
 This tool executes the query associated with a saved Look and
 returns the resulting data in a JSON structure.

 Parameters:
 - look_id (required): The unique identifier of the Look to run,
 typically obtained from the `get_looks` tool.

 Output:
 The query results are returned as a JSON object.

Reference

field	type	required	description
type	string	true	Must be “looker-run-look”
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

looker-update-project-file

Mon, 01 Jan 0001 00:00:00 +0000

About

A looker-update-project-file tool updates the content of a LookML file.

looker-update-project-file accepts a project_id parameter and a file_path parameter as well as the new file content.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

kind: tool
name: update_project_file
type: looker-update-project-file
source: looker-source
description: |
 This tool modifies the content of an existing LookML file within a specified project.

 Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.

 Parameters:
 - project_id (required): The unique ID of the LookML project.
 - file_path (required): The exact path to the LookML file to modify within the project.
 - content (required): The new, complete LookML content to overwrite the existing file.

 Output:
 A confirmation message upon successful file modification.

Reference

field	type	required	description
type	string	true	Must be “looker-update-project-file”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

looker-validate-project

Mon, 01 Jan 0001 00:00:00 +0000

About

A “looker-validate-project” tool checks the syntax of a LookML project and reports any errors

looker-validate-project accepts a project_id parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Looker

Example

tools:
 validate_project:
 kind: looker-validate-project
 source: looker-source
 description: |
 This tool checks a LookML project for syntax errors.

 Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.

 Parameters:
 - project_id (required): The unique ID of the LookML project.

 Output:
 A list of error details including the file path and line number, and also a list of models
 that are not currently valid due to LookML errors.

Reference

field	type	required	description
kind	string	true	Must be “looker-validate-project”.
source	string	true	Name of the source Looker instance.
description	string	true	Description of the tool that is passed to the LLM.

mindsdb-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A mindsdb-execute-sql tool executes a SQL statement against a MindsDB federated database.

mindsdb-execute-sql takes one input parameter sql and runs the SQL statement against the source. This tool enables you to:

Query Multiple Datasources: Execute SQL across hundreds of connected datasources
Cross-Datasource Joins: Perform joins between different databases, APIs, and file systems
ML Model Predictions: Query ML models as virtual tables for real-time predictions
Unstructured Data: Query documents, images, and other unstructured data as structured tables
Federated Analytics: Perform analytics across multiple datasources simultaneously
API Translation: Automatically translate SQL queries into REST APIs, GraphQL, and native protocols

Compatible Sources

This tool can be used with the following database sources:

mindsdb-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A mindsdb-sql tool executes a pre-defined SQL statement against a MindsDB federated database.

The specified SQL statement is executed as a prepared statement, and expects parameters in the SQL query to be in the form of placeholders ?.

This tool enables you to:

Query Multiple Datasources: Execute parameterized SQL across hundreds of connected datasources
Cross-Datasource Joins: Perform joins between different databases, APIs, and file systems
ML Model Predictions: Query ML models as virtual tables for real-time predictions
Unstructured Data: Query documents, images, and other unstructured data as structured tables
Federated Analytics: Perform analytics across multiple datasources simultaneously
API Translation: Automatically translate SQL queries into REST APIs, GraphQL, and native protocols

Compatible Sources

This tool can be used with the following database sources:

mongodb-aggregate

Mon, 01 Jan 0001 00:00:00 +0000

About

The mongodb-aggregate tool is the most powerful query tool for MongoDB, allowing you to process data through a multi-stage pipeline. Each stage transforms the documents as they pass through, enabling complex operations like grouping, filtering, reshaping documents, and performing calculations.

The core of this tool is the pipelinePayload, which must be a string containing a JSON array of pipeline stage documents. The tool returns a JSON array of documents produced by the final stage of the pipeline.

mongodb-delete-many

Mon, 01 Jan 0001 00:00:00 +0000

About

The mongodb-delete-many tool performs a bulk destructive operation, deleting ALL documents from a collection that match a specified filter.

The tool returns the total count of documents that were deleted. If the filter does not match any documents (i.e., the deleted count is 0), the tool will return an error.

Compatible Sources

This tool can be used with the following database sources:

Source Name
MongoDB

Example

Here is an example that performs a cleanup task by deleting all products from the inventory collection that belong to a discontinued brand.

mongodb-delete-one

Mon, 01 Jan 0001 00:00:00 +0000

About

The mongodb-delete-one tool performs a destructive operation, deleting the first single document that matches a specified filter from a MongoDB collection.

If the filter matches multiple documents, only the first one found by the database will be deleted. This tool is useful for removing specific entries, such as a user account or a single item from an inventory based on a unique ID.

The tool returns the number of documents deleted, which will be either 1 if a document was found and deleted, or 0 if no matching document was found.

mongodb-find

Mon, 01 Jan 0001 00:00:00 +0000

About

A mongodb-find tool is used to query a MongoDB collection and retrieve documents that match a specified filter. It’s a flexible tool that allows you to shape the output by selecting specific fields (projection), ordering the results (sorting), and restricting the number of documents returned (limiting).

The tool returns a JSON array of the documents found.

Compatible Sources

This tool can be used with the following database sources:

Source Name
MongoDB

Example

Here’s an example that finds up to 10 users from the customers collection who live in a specific city. The results are sorted by their last name, and only their first name, last name, and email are returned.

mongodb-find-one

Mon, 01 Jan 0001 00:00:00 +0000

About

A mongodb-find-one tool is used to retrieve the first single document that matches a specified filter from a MongoDB collection. If multiple documents match the filter, you can use sort options to control which document is returned. Otherwise, the selection is not guaranteed.

The tool returns a single JSON object representing the document, wrapped in a JSON array.

Compatible Sources

This tool can be used with the following database sources:

mongodb-insert-many

Mon, 01 Jan 0001 00:00:00 +0000

About

The mongodb-insert-many tool inserts multiple new documents into a specified MongoDB collection in a single bulk operation. This is highly efficient for adding large amounts of data at once.

This tool takes one required parameter named data. This data parameter must be a string containing a JSON array of document objects. Upon successful insertion, the tool returns a JSON array containing the unique _id of each new document that was created.

mongodb-insert-one

Mon, 01 Jan 0001 00:00:00 +0000

About

The mongodb-insert-one tool inserts a single new document into a specified MongoDB collection.

This tool takes one required parameter named data, which must be a string containing the JSON object you want to insert. Upon successful insertion, the tool returns the unique _id of the newly created document.

Compatible Sources

This tool can be used with the following database sources:

Source Name
MongoDB

Example

Here is an example configuration for a tool that adds a new user to a users collection.

mongodb-update-many

Mon, 01 Jan 0001 00:00:00 +0000

About

A mongodb-update-many tool updates all documents within a specified MongoDB collection that match a given filter. It locates the documents using a filterPayload and applies the modifications defined in an updatePayload.

The tool returns an array of three integers: [ModifiedCount, UpsertedCount, MatchedCount].

Compatible Sources

This tool can be used with the following database sources:

Source Name
MongoDB

Example

Here’s an example configuration. This tool applies a discount to all items within a specific category and also marks them as being on sale.

mongodb-update-one

Mon, 01 Jan 0001 00:00:00 +0000

About

A mongodb-update-one tool updates a single document within a specified MongoDB collection. It locates the document to be updated using a filterPayload and applies modifications defined in an updatePayload. If the filter matches multiple documents, only the first one found will be updated.

Compatible Sources

This tool can be used with the following database sources:

Source Name
MongoDB

Example

Here’s an example of a mongodb-update-one tool configuration. This tool updates the stock and status fields of a document in the inventory collection where the item field matches a provided value. If no matching document is found, the upsert: true option will create a new one.

mssql-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A mssql-execute-sql tool executes a SQL statement against a SQL Server database. It’s compatible with any of the following sources:

mssql-execute-sql takes one input parameter sql and run the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
SQL Server
Cloud SQL for SQL Server

Example

kind: tool
name: execute_sql_tool
type: mssql-execute-sql
source: my-mssql-instance
description: Use this tool to execute sql statement.

Reference

field	type	required	description
type	string	true	Must be “mssql-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

mssql-list-tables

Mon, 01 Jan 0001 00:00:00 +0000

About

The mssql-list-tables tool retrieves schema information for all or specified tables in a SQL server database.

mssql-list-tables lists detailed schema information (object type, columns, constraints, indexes, triggers, owner, comment) as JSON for user-created tables (ordinary or partitioned).

The tool takes the following input parameters:

table_names (string, optional): Filters by a comma-separated list of names. By default, it lists all tables in user schemas. Default: "".
output_format (string, optional): Indicate the output format of table schema. simple will return only the table names, detailed will return the full table information. Default: detailed.

Compatible Sources

This tool can be used with the following database sources:

mssql-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A mssql-sql tool executes a pre-defined SQL statement against a SQL Server database.

Toolbox supports the prepare statement syntax of MS SQL Server and expects parameters in the SQL query to be in the form of either @Name or @p1 to @pN (ordinal position).

db.QueryContext(ctx, `select * from t where ID = @ID and Name = @p2;`, sql.Named("ID", 6), "Bob")

Compatible Sources

This tool can be used with the following database sources:

Source Name
SQL Server
Cloud SQL for SQL Server

Example

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

mysql-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A mysql-execute-sql tool executes a SQL statement against a MySQL database.

mysql-execute-sql takes one input parameter sql and run the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
MySQL
Cloud SQL for MySQL

Example

kind: tool
name: execute_sql_tool
type: mysql-execute-sql
source: my-mysql-instance
description: Use this tool to execute sql statement.

Reference

field	type	required	description
type	string	true	Must be “mysql-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

mysql-get-query-plan

Mon, 01 Jan 0001 00:00:00 +0000

About

A mysql-get-query-plan tool gets the execution plan for a SQL statement against a MySQL database.

mysql-get-query-plan takes one input parameter sql_statement and gets the execution plan for the SQL statement against the source.

Compatible Sources

This tool can be used with the following database sources:

Source Name
MySQL
Cloud SQL for MySQL

Example

kind: tool
name: get_query_plan_tool
type: mysql-get-query-plan
source: my-mysql-instance
description: Use this tool to get the execution plan for a sql statement.

Reference

field	type	required	description
type	string	true	Must be “mysql-get-query-plan”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

mysql-list-active-queries

Mon, 01 Jan 0001 00:00:00 +0000

About

A mysql-list-active-queries tool retrieves information about active queries in a MySQL database.

mysql-list-active-queries outputs detailed information as JSON for current active queries, ordered by execution time in descending order. This tool takes 2 optional input parameters:

min_duration_secs (optional): Only show queries running for at least this long in seconds, default 0.
limit (optional): max number of queries to return, default 10.

Compatible Sources

This tool can be used with the following database sources:

mysql-list-table-fragmentation

Mon, 01 Jan 0001 00:00:00 +0000

About

A mysql-list-table-fragmentation tool checks table fragmentation of MySQL tables by calculating the size of the data and index files in bytes and comparing with free space allocated to each table. This tool calculates fragmentation_percentage which represents the proportion of free space relative to the total data and index size.

mysql-list-table-fragmentation outputs detailed information as JSON , ordered by the fragmentation percentage in descending order. This tool takes 4 optional input parameters:

mysql-list-tables

Mon, 01 Jan 0001 00:00:00 +0000

About

The mysql-list-tables tool retrieves schema information for all or specified tables in a MySQL database.

mysql-list-tables lists detailed schema information (object type, columns, constraints, indexes, triggers, owner, comment) as JSON for user-created tables (ordinary or partitioned). Filters by a comma-separated list of names. If names are omitted, it lists all tables in user schemas. The output format can be set to simple which will return only the table names or detailed which is the default.

mysql-list-tables-missing-unique-indexes

Mon, 01 Jan 0001 00:00:00 +0000

About

A mysql-list-tables-missing-unique-indexes tool searches tables that do not have primary or unique indices in a MySQL database.

mysql-list-tables-missing-unique-indexes outputs table names, including table_schema and table_name in JSON format. It takes 2 optional input parameters:

table_schema (optional): Only check tables in this specific schema/database. Search all visible tables in all visible databases if not specified.
limit (optional): max number of queries to return, default 50.

Compatible Sources

This tool can be used with the following database sources:

mysql-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A mysql-sql tool executes a pre-defined SQL statement against a MySQL database.

The specified SQL statement is executed as a prepared statement, and expects parameters in the SQL query to be in the form of placeholders ?.

Compatible Sources

This tool can be used with the following database sources:

Source Name
MySQL
Cloud SQL for MySQL

Example

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

neo4j-cypher

Mon, 01 Jan 0001 00:00:00 +0000

About

A neo4j-cypher tool executes a pre-defined Cypher statement against a Neo4j database.

The specified Cypher statement is executed as a parameterized statement, and specified parameters will be used according to their name: e.g. $id.

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

neo4j-execute-cypher

Mon, 01 Jan 0001 00:00:00 +0000

About

A neo4j-execute-cypher tool executes an arbitrary Cypher query provided as a string parameter against a Neo4j database. It’s designed to be a flexible tool for interacting with the database when a pre-defined query is not sufficient.

For security, the tool can be configured to be read-only. If the readOnly flag is set to true, the tool will analyze the incoming Cypher query and reject any write operations (like CREATE, MERGE, DELETE, etc.) before execution.

neo4j-schema

Mon, 01 Jan 0001 00:00:00 +0000

About

A neo4j-schema tool connects to a Neo4j database and extracts its complete schema information. It runs multiple queries concurrently to efficiently gather details about node labels, relationships, properties, constraints, and indexes.

The tool automatically detects if the APOC (Awesome Procedures on Cypher) library is available. If so, it uses APOC procedures like apoc.meta.schema for a highly detailed overview of the database structure; otherwise, it falls back to using native Cypher queries.

oceanbase-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

An oceanbase-execute-sql tool executes a SQL statement against an OceanBase database.

oceanbase-execute-sql takes one input parameter sql and runs the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
OceanBase

Example

kind: tool
name: execute_sql_tool
type: oceanbase-execute-sql
source: my-oceanbase-instance
description: Use this tool to execute sql statement.

Reference

field	type	required	description
type	string	true	Must be “oceanbase-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

oceanbase-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

An oceanbase-sql tool executes a pre-defined SQL statement against an OceanBase database.

The specified SQL statement is executed as a prepared statement, and expects parameters in the SQL query to be in the form of placeholders ?.

Compatible Sources

This tool can be used with the following database sources:

Source Name
OceanBase

Example

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

oracle-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

An oracle-execute-sql tool executes a SQL statement against an Oracle database.

oracle-execute-sql takes one input parameter sql and runs the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Oracle

Example

kind: tool
name: execute_sql_tool
type: oracle-execute-sql
source: my-oracle-instance
description: Use this tool to execute sql statement.

oracle-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

An oracle-sql tool executes a pre-defined SQL statement against an Oracle database.

By default, tools are configured as read-only (SAFE mode). To execute data modification statements (INSERT, UPDATE, DELETE), you must explicitly set the readOnly field to false.

Compatible Sources

This tool can be used with the following database sources:

postgres-database-overview

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-database-overview fetches the current state of the PostgreSQL server.

postgres-database-overview fetches the current state of the PostgreSQL server This tool does not take any input parameters.

Compatible Sources

This tool can be used with the following database sources:

Source Name
PostgreSQL
AlloyDB PostgreSQL
Cloud SQL for PostgreSQL

Example

kind: tool
name: database_overview
type: postgres-database-overview
source: cloudsql-pg-source
description: |
 fetches the current state of the PostgreSQL server. It returns the postgres version, whether it's a replica, uptime duration, maximum connection limit, number of current connections, number of active connections and the percentage of connections in use.

The response is a JSON object with the following elements:

postgres-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A postgres-execute-sql tool executes a SQL statement against a Postgres database.

postgres-execute-sql takes one input parameter sql and run the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
PostgreSQL
AlloyDB PostgreSQL
Cloud SQL for PostgreSQL

Example

kind: tool
name: execute_sql_tool
type: postgres-execute-sql
source: my-pg-instance
description: Use this tool to execute sql statement.

Reference

field	type	required	description
type	string	true	Must be “postgres-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

postgres-get-column-cardinality

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-get-column-cardinality tool estimates the number of unique values (cardinality) for one or all columns in a specific PostgreSQL table by using the database’s internal statistics.

postgres-get-column-cardinality returns detailed information as JSON about column cardinality values, ordered by estimated cardinality in descending order. The tool takes the following input parameters:

schema_name (required): The schema name in which the table is present.
table_name (required): The table name in which the column is present.
column_name (optional): The column name for which the cardinality is to be found. If not provided, cardinality for all columns will be returned. Default: "".

Compatible Sources

This tool can be used with the following database sources:

postgres-list-active-queries

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-active-queries tool retrieves information about currently active queries in a Postgres database.

postgres-list-active-queries lists detailed information as JSON for currently active queries. The tool takes the following input parameters:

min_duraton (optional): Only show queries running at least this long (e.g., ‘1 minute’, ‘1 second’, ‘2 seconds’). Default: ‘1 minute’.
exclude_application_names (optional): A comma-separated list of application names to exclude from the query results. This is useful for filtering out queries from specific applications (e.g., ‘psql’, ‘pgAdmin’, ‘DBeaver’). The match is case-sensitive. Whitespace around commas and names is automatically handled. If this parameter is omitted, no applications are excluded.
limit (optional): The maximum number of rows to return. Default: 50.

Compatible Sources

This tool can be used with the following database sources:

postgres-list-available-extensions

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-available-extensions tool retrieves all PostgreSQL extensions available for installation on a Postgres database.

postgres-list-available-extensions lists all PostgreSQL extensions available for installation (extension name, default version description) as JSON. The does not support any input parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
PostgreSQL
AlloyDB PostgreSQL
Cloud SQL for PostgreSQL

Example

kind: tool
name: list_available_extensions
type: postgres-list-available-extensions
source: postgres-source
description: Discover all PostgreSQL extensions available for installation on this server, returning name, default_version, and description.

Reference

name	default_version	description
address_standardizer	3.5.2	Used to parse an address into constituent elements. Generally used to support geocoding address normalization step.
amcheck	1.4	functions for verifying relation integrity
anon	1.0.0	Data anonymization tools
autoinc	1.0	functions for autoincrementing fields

postgres-list-database-stats

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-database-stats lists the key performance and activity statistics for each PostgreSQL database in the instance, offering insights into cache efficiency, transaction throughput, row-level activity, temporary file usage, and contention.

postgres-list-database-stats lists detailed information as JSON for each database. The tool takes the following input parameters:

database_name (optional): A text to filter results by database name. Default: ""
include_templates (optional): Boolean, set to true to include template databases in the results. Default: false
database_owner (optional): A text to filter results by database owner. Default: ""
default_tablespace (optional): A text to filter results by the default tablespace name. Default: ""
order_by (optional): Specifies the sorting order. Valid values are 'size' (descending) or 'commit' (descending). Default: database_name ascending.
limit (optional): The maximum number of databases to return. Default: 10

Compatible Sources

This tool can be used with the following database sources:

postgres-list-indexes

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-indexes tool lists available user indexes in the database excluding those in pg_catalog and information_schema.

postgres-list-indexes lists detailed information as JSON for indexes. The tool takes the following input parameters:

table_name (optional): A text to filter results by table name. Default: ""
index_name (optional): A text to filter results by index name. Default: ""
schema_name (optional): A text to filter results by schema name. Default: ""
only_unused (optional): If true, returns indexes that have never been used.
limit (optional): The maximum number of rows to return. Default: 50.

Compatible Sources

This tool can be used with the following database sources:

postgres-list-installed-extensions

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-installed-extensions tool retrieves all PostgreSQL extensions installed on a Postgres database.

postgres-list-installed-extensions lists all installed PostgreSQL extensions (extension name, version, schema, owner, description) as JSON. The does not support any input parameter.

Compatible Sources

This tool can be used with the following database sources:

Source Name
PostgreSQL
AlloyDB PostgreSQL
Cloud SQL for PostgreSQL

Example

kind: tool
name: list_installed_extensions
type: postgres-list-installed-extensions
source: postgres-source
description: List all installed PostgreSQL extensions with their name, version, schema, owner, and description.

Reference

field	type	required	description
type	string	true	Must be “postgres-list-active-queries”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

postgres-list-locks

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-locks tool displays information about active locks by joining pg_stat_activity with pg_locks. This is useful to find transactions holding or waiting for locks and to troubleshoot contention.

This tool identifies all locks held by active processes showing the process ID, user, query text, and an aggregated list of all transactions and specific locks (relation, mode, grant status) associated with each process.

Compatible Sources

This tool can be used with the following database sources:

postgres-list-pg-settings

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-pg-settings tool lists the configuration parameters for the postgres server, their current values, and related information.

postgres-list-pg-settings lists detailed information as JSON for each setting. The tool takes the following input parameters:

setting_name (optional): A text to filter results by setting name. Default: ""
limit (optional): The maximum number of rows to return. Default: 50.

Compatible Sources

This tool can be used with the following database sources:

Source Name
PostgreSQL
AlloyDB PostgreSQL
Cloud SQL for PostgreSQL

Example

kind: tool
name: list_indexes
type: postgres-list-pg-settings
source: postgres-source
description: |
 Lists configuration parameters for the postgres server ordered lexicographically, 
 with a default limit of 50 rows. It returns the parameter name, its current setting,
 unit of measurement, a short description, the source of the current setting (e.g.,
 default, configuration file, session), and whether a restart is required when the
 parameter value is changed."

The response is a json array with the following elements:

postgres-list-publication-tables

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-publication-tables tool lists all publication tables in the database.

postgres-list-publication-tables lists detailed information as JSON for publication tables. A publication table in PostgreSQL is a table that is explicitly included as a source for replication within a publication (a set of changes generated from a table or group of tables) as part of the logical replication feature. The tool takes the following input parameters:

table_names (optional): Filters by a comma-separated list of table names. Default: ""
publication_names (optional): Filters by a comma-separated list of publication names. Default: ""
schema_names (optional): Filters by a comma-separated list of schema names. Default: ""
limit (optional): The maximum number of rows to return. Default: 50

Compatible Sources

This tool can be used with the following database sources:

postgres-list-query-stats

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-query-stats tool retrieves query statistics from the pg_stat_statements extension in a PostgreSQL database. It provides detailed performance metrics for executed queries.

postgres-list-query-stats lists detailed query statistics as JSON, ordered by total execution time in descending order. The tool takes the following input parameters:

database_name (optional): The database name to filter query stats for. The input is used within a LIKE clause. Default: "" (all databases).
limit (optional): The maximum number of results to return. Default: 50.

Compatible Sources

This tool can be used with the following database sources:

postgres-list-roles

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-roles tool lists all the user-created roles in the instance, excluding system roles (like cloudsql% or pg_%). It provides details about each role’s attributes and memberships.

postgres-list-roles lists detailed information as JSON for each role. The tool takes the following input parameters:

role_name (optional): A text to filter results by role name. Default: ""
limit (optional): The maximum number of roles to return. Default: 50

Compatible Sources

This tool can be used with the following database sources:

postgres-list-schemas

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-schemas tool retrieves information about schemas in a database excluding system and temporary schemas.

postgres-list-schemas lists detailed information as JSON for each schema. The tool takes the following input parameters:

schema_name (optional): A text to filter results by schema name. Default: ""
owner (optional): A text to filter results by owner name. Default: ""
limit (optional): The maximum number of rows to return. Default: 50.

Compatible Sources

This tool can be used with the following database sources:

postgres-list-sequences

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-sequences tool retrieves information about sequences in a Postgres database.

postgres-list-sequences lists detailed information as JSON for all sequences. The tool takes the following input parameters:

sequence_name (optional): A text to filter results by sequence name. The input is used within a LIKE clause. Default: ""
schema_name (optional): A text to filter results by schema name. The input is used within a LIKE clause. Default: ""
limit (optional): The maximum number of rows to return. Default: 50.

Compatible Sources

This tool can be used with the following database sources:

postgres-list-stored-procedure

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-stored-procedure tool queries PostgreSQL system catalogs (pg_proc, pg_namespace, pg_roles, and pg_language) to retrieve comprehensive metadata about stored procedures in the database. It filters for procedures (kind = ‘p’) and provides the full procedure definition along with ownership and language information.

The tool returns a JSON array where each element represents a stored procedure with its schema, name, owner, language, complete definition, and optional description. Results are sorted by schema name and procedure name, with a default limit of 20 procedures.

postgres-list-table-stats

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-table-stats tool queries pg_stat_all_tables to provide comprehensive statistics about tables in the database. It calculates useful metrics like index scan ratio and dead row ratio to help identify performance issues and table bloat.

The tool returns a JSON array where each element represents statistics for a table, including scan metrics, row counts, and vacuum history. Results are sorted by sequential scans by default and limited to 50 rows.

postgres-list-tables

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-tables tool retrieves schema information for all or specified tables in a Postgres database.

postgres-list-tables lists detailed schema information (object type, columns, constraints, indexes, triggers, owner, comment) as JSON for user-created tables (ordinary or partitioned). The tool takes the following input parameters: * table_names (optional): Filters by a comma-separated list of names. By default, it lists all tables in user schemas.* output_format (optional): Indicate the output format of table schema. simple will return only the table names, detailed will return the full table information. Default: detailed.

postgres-list-tablespaces

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-tablespaces tool lists available tablespaces in the database.

postgres-list-tablespaces lists detailed information as JSON for tablespaces. The tool takes the following input parameters:

tablespace_name (optional): A text to filter results by tablespace name. Default: ""
limit (optional): The maximum number of tablespaces to return. Default: 50

Compatible Sources

This tool can be used with the following database sources:

Source Name
PostgreSQL
AlloyDB PostgreSQL
Cloud SQL for PostgreSQL

Example

kind: tool
name: list_tablespaces
type: postgres-list-tablespaces
source: postgres-source
description: |
 Lists all tablespaces in the database. Returns the tablespace name,
 owner name, size in bytes(if the current user has CREATE privileges on
 the tablespace, otherwise NULL), internal object ID, the access control
 list regarding permissions, and any specific tablespace options.

The response is a json array with the following elements:

postgres-list-triggers

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-triggers tool lists available non-internal triggers in the database.

postgres-list-triggers lists detailed information as JSON for triggers. The tool takes the following input parameters:

trigger_name (optional): A text to filter results by trigger name. The input is used within a LIKE clause. Default: ""
schema_name (optional): A text to filter results by schema name. The input is used within a LIKE clause. Default: ""
table_name (optional): A text to filter results by table name. The input is used within a LIKE clause. Default: ""
limit (optional): The maximum number of triggers to return. Default: 50

Compatible Sources

This tool can be used with the following database sources:

postgres-list-views

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-list-views tool retrieves a list of top N (default 50) views from a Postgres database, excluding those in system schemas (pg_catalog, information_schema).

postgres-list-views lists detailed view information (schemaname, viewname, ownername, definition) as JSON for views in a database. The tool takes the following input parameters:

view_name (optional): A string pattern to filter view names. Default: ""
schema_name (optional): A string pattern to filter schema names. Default: ""
limit (optional): The maximum number of rows to return. Default: 50.

Compatible Sources

This tool can be used with the following database sources:

postgres-long-running-transactions

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-long-running-transactions tool reports transactions that exceed a configured duration threshold by scanning pg_stat_activity for sessions where xact_start is set and older than the configured interval.

The tool returns a JSON array with one object per matching session (non-idle). Each object contains the process id, database and user, application name, client address, session state, several age intervals (connection, transaction, query, and last activity), wait event info, and the SQL text currently associated with the session.

postgres-replication-stats

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-replication-stats tool queries pg_stat_replication to surface the status of connected replicas. It reports application_name, client address, connection and sync state, and human-readable lag sizes (sent, write, flush, replay, and total) computed using WAL LSN differences.

This tool takes no parameters. It returns a JSON array; each element represents a replication connection on the primary and includes lag metrics formatted by pg_size_pretty.

Compatible Sources

This tool can be used with the following database sources:

postgres-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A postgres-sql tool executes a pre-defined SQL statement against a Postgres database. The specified SQL statement is executed as a prepared statement, and specified parameters will be inserted according to their position: e.g. $1 will be the first parameter specified, $2 will be the second parameter, and so on. If template parameters are included, they will be resolved before execution of the prepared statement.

Compatible Sources

This tool can be used with the following database sources:

Quickstart (Local with BigQuery)

Mon, 01 Jan 0001 00:00:00 +0000

Before you begin

This guide assumes you have already done the following:

Installed Python 3.10+ (including pip and your preferred virtual environment tool for managing dependencies e.g. venv).
Installed and configured the Google Cloud SDK (gcloud CLI).
Authenticated with Google Cloud for Application Default Credentials (ADC):
```
gcloud auth login --update-adc
```
Set your default Google Cloud project (replace YOUR_PROJECT_ID with your actual project ID):
```
gcloud config set project YOUR_PROJECT_ID
export GOOGLE_CLOUD_PROJECT=YOUR_PROJECT_ID
```
Toolbox and the client libraries will use this project for BigQuery, unless overridden in configurations.

Quickstart (MCP with Neo4j)

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Model Context Protocol is an open protocol that standardizes how applications provide context to LLMs. Check out this page on how to connect to Toolbox via MCP.

Step 1: Set up your Neo4j Database and Data

In this section, you’ll set up a database and populate it with sample data for a movies-related agent. This guide assumes you have a running Neo4j instance, either locally or in the cloud.

. Populate the database with data. To make this quickstart straightforward, we’ll use the built-in Movies dataset available in Neo4j.

redis

Mon, 01 Jan 0001 00:00:00 +0000

About

A redis tool executes a series of pre-defined Redis commands against a Redis source.

The specified Redis commands are executed sequentially. Each command is represented as a string list, where the first element is the command name (e.g., SET, GET, HGETALL) and subsequent elements are its arguments.

Dynamic Command Parameters

Command arguments can be templated using the $variableName annotation. The array type parameters will be expanded once into multiple arguments. Take the following config for example:

serverless-spark-get-batch

Mon, 01 Jan 0001 00:00:00 +0000

About

The serverless-spark-get-batch tool allows you to retrieve a specific Serverless Spark batch job.

serverless-spark-list-batches accepts the following parameters:

name: The short name of the batch, e.g. for projects/my-project/locations/us-central1/my-batch, pass my-batch.

The tool gets the project and location from the source configuration.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Serverless for Apache Spark

Example

kind: tool
name: get_my_batch
type: serverless-spark-get-batch
source: my-serverless-spark-source
description: Use this tool to get a serverless spark batch.

Output Format

The response contains the full Batch object as defined in the API spec, plus additional fields consoleUrl and logsUrl where a human can go for more detailed information.

serverless-spark-get-session-template

Mon, 01 Jan 0001 00:00:00 +0000

About

A serverless-spark-get-session-template tool retrieves a specific Spark session template from a Google Cloud Serverless for Apache Spark source.

serverless-spark-get-session-template accepts the following parameters:

name (required): The short name of the session template, e.g. for projects/my-project/locations/us-central1/sessionTemplates/my-session-template, pass my-session-template.

The tool gets the project and location from the source configuration.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Serverless for Apache Spark

Example

kind: tool
name: get_spark_session_template
type: serverless-spark-get-session-template
source: my-serverless-spark-source
description: Use this tool to get details of a serverless spark session template.

Output Format

{
 "sessionTemplate": { 
 "name": "projects/my-project/locations/us-central1/sessionTemplates/my-session-template",
 "description": "Template for Spark Session",
 // ... complete session template resource definition
 }
}

Reference

field	type	required	description
type	string	true	Must be “serverless-spark-get-session-template”.
source	string	true	Name of the source the tool should use.
description	string	true	Description of the tool that is passed to the LLM.
authRequired	string[]	false	List of auth services required to invoke this tool

serverless-spark-list-batches

Mon, 01 Jan 0001 00:00:00 +0000

About

A serverless-spark-list-batches tool returns a list of Spark batches from a Google Cloud Serverless for Apache Spark source.

serverless-spark-list-batches accepts the following parameters:

filter (optional): A filter expression to limit the batches returned. Filters are case sensitive and may contain multiple clauses combined with logical operators (AND/OR). Supported fields are batch_id, batch_uuid, state, create_time, and labels. For example: state = RUNNING AND create_time < "2023-01-01T00:00:00Z".
pageSize (optional): The maximum number of batches to return in a single page.
pageToken (optional): A page token, received from a previous call, to retrieve the next page of results.

The tool gets the project and location from the source configuration.

singlestore-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A singlestore-execute-sql tool executes a SQL statement against a SingleStore database.

singlestore-execute-sql takes one input parameter sql and runs the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
SingleStore

Example

kind: tool
name: execute_sql_tool
type: singlestore-execute-sql
source: my-s2-instance
description: Use this tool to execute sql statement

Reference

field	type	required	description
type	string	true	Must be “singlestore-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

singlestore-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A singlestore-execute-sql tool executes a SQL statement against a SingleStore database.

The specified SQL statement expects parameters in the SQL query to be in the form of placeholders ?.

Compatible Sources

This tool can be used with the following database sources:

Source Name
SingleStore

Example

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

snowflake-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A snowflake-execute-sql tool executes a SQL statement against a Snowflake database.

snowflake-execute-sql takes one input parameter sql and run the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Snowflake

Example

kind: tool
name: execute_sql_tool
type: snowflake-execute-sql
source: my-snowflake-instance
description: Use this tool to execute sql statement.

Reference

field	type	required	description
type	string	true	Must be “snowflake-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.
authRequired	array[string]	false	List of auth services that are required to use this tool.

snowflake-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A snowflake-sql tool executes a pre-defined SQL statement against a Snowflake database.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Snowflake

The specified SQL statement is executed as a prepared statement, and specified parameters will be inserted according to their position: e.g. :1 will be the first parameter specified, :2 will be the second parameter, and so on.

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

AlloyDB Admin Source

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-admin source provides a client to interact with the Google AlloyDB API. This allows tools to perform administrative tasks on AlloyDB resources, such as managing clusters, instances, and users.

Authentication can be handled in two ways:

Application Default Credentials (ADC): By default, the source uses ADC to authenticate with the API.
Client-side OAuth: If useClientOAuth is set to true, the source will expect an OAuth 2.0 access token to be provided by the client (e.g., a web browser) for each request.

Available Tools

AlloyDB Admin Source Tools

Tool Name	Description
alloydb-create-cluster	The "alloydb-create-cluster" tool creates a new AlloyDB for PostgreSQL cluster in a specified project and location.
alloydb-create-instance	The "alloydb-create-instance" tool creates a new AlloyDB instance within a specified cluster.
alloydb-get-cluster	The "alloydb-get-cluster" tool retrieves details for a specific AlloyDB cluster.
alloydb-get-instance	The "alloydb-get-instance" tool retrieves details for a specific AlloyDB instance.
alloydb-get-user	The "alloydb-get-user" tool retrieves details for a specific AlloyDB user.
alloydb-list-clusters	The "alloydb-list-clusters" tool lists the AlloyDB clusters in a given project and location.
alloydb-list-instances	The "alloydb-list-instances" tool lists the AlloyDB instances for a given project, cluster and location.
alloydb-list-users	The "alloydb-list-users" tool lists all database users within an AlloyDB cluster.
alloydb-create-user	The "alloydb-create-user" tool creates a new database user within a specified AlloyDB cluster.
alloydb-wait-for-operation	Wait for a long-running AlloyDB operation to complete.

Example

kind: source
name: my-alloydb-admin
type: alloydb-admin
---
kind: source
name: my-oauth-alloydb-admin
type: alloydb-admin
useClientOAuth: true

Reference

field	type	required	description
type	string	true	Must be “alloydb-admin”.
defaultProject	string	false	The Google Cloud project ID to use for AlloyDB infrastructure tools.
useClientOAuth	boolean	false	If true, the source will use client-side OAuth for authorization. Otherwise, it will use Application Default Credentials. Defaults to `false`.

AlloyDB for PostgreSQL Source

Mon, 01 Jan 0001 00:00:00 +0000

About

AlloyDB for PostgreSQL is a fully-managed, PostgreSQL-compatible database for demanding transactional workloads. It provides enterprise-grade performance and availability while maintaining 100% compatibility with open-source PostgreSQL.

If you are new to AlloyDB for PostgreSQL, you can create a free trial cluster.

Available Tools

AlloyDB for PostgreSQL Source Tools

Tool Name	Description
alloydb-ai-nl	The "alloydb-ai-nl" tool leverages [AlloyDB AI](https://cloud.google.com/alloydb/ai) next-generation Natural Language support to provide the ability to query the database directly using natural language.

AlloyDB for PostgreSQL Source maintains full compatibility with PostgreSQL, allowing you to use the following tools with this connection:

BigQuery Source

Mon, 01 Jan 0001 00:00:00 +0000

About

BigQuery is Google Cloud’s fully managed, petabyte-scale, and cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near real time. With BigQuery, there’s no infrastructure to set up or manage, letting you focus on finding meaningful insights using GoogleSQL and taking advantage of flexible pricing models across on-demand and flat-rate options.

If you are new to BigQuery, you can try to load and query data with the bq tool.

Bigtable Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Bigtable is a low-latency NoSQL database service for machine learning, operational analytics, and user-facing operations. It’s a wide-column, key-value store that can scale to billions of rows and thousands of columns. With Bigtable, you can replicate your data to regions across the world for high availability and data resiliency.

If you are new to Bigtable, you can try to create an instance and write data with the cbt CLI.

You can use GoogleSQL statements to query your Bigtable data. GoogleSQL is an ANSI-compliant structured query language (SQL) that is also implemented for other Google Cloud services. SQL queries are handled by cluster nodes in the same way as NoSQL data requests. Therefore, the same best practices apply when creating SQL queries to run against your Bigtable data, such as avoiding full table scans or complex filters.

Cassandra Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Apache Cassandra is a NoSQL distributed database. By design, NoSQL databases are lightweight, open-source, non-relational, and largely distributed. Counted among their strengths are horizontal scalability, distributed architectures, and a flexible approach to schema definition.

Available Tools

Cassandra Source Tools

Tool Name	Description
cassandra-cql	A "cassandra-cql" tool executes a pre-defined CQL statement against a Cassandra database.

Example

kind: source
name: my-cassandra-source
type: cassandra
hosts:
 - 127.0.0.1
keyspace: my_keyspace
protoVersion: 4
username: ${USER_NAME}
password: ${PASSWORD}
caPath: /path/to/ca.crt # Optional: path to CA certificate
certPath: /path/to/client.crt # Optional: path to client certificate
keyPath: /path/to/client.key # Optional: path to client key
enableHostVerification: true # Optional: enable host verification

Tip

ClickHouse Source

Mon, 01 Jan 0001 00:00:00 +0000

About

ClickHouse is a fast, open-source, column-oriented database

Available Tools

ClickHouse Source Tools

Tool Name	Description
clickhouse-execute-sql	A "clickhouse-execute-sql" tool executes a SQL statement against a ClickHouse database.
clickhouse-sql	A "clickhouse-sql" tool executes SQL queries as prepared statements in ClickHouse.
clickhouse-list-databases	A "clickhouse-list-databases" tool lists all databases in a ClickHouse instance.
clickhouse-list-tables	A "clickhouse-list-tables" tool lists all tables in a specific ClickHouse database.

Requirements

Database User

This source uses standard ClickHouse authentication. You will need to create a ClickHouse user (or with ClickHouse Cloud) to connect to the database with. The user should have appropriate permissions for the operations you plan to perform.

Cloud SQL Admin Source

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-admin source provides a client to interact with the Google Cloud SQL Admin API. This allows tools to perform administrative tasks on Cloud SQL instances, such as creating users and databases.

Authentication can be handled in two ways:

Application Default Credentials (ADC): By default, the source uses ADC to authenticate with the API.
Client-side OAuth: If useClientOAuth is set to true, the source will expect an OAuth 2.0 access token to be provided by the client (e.g., a web browser) for each request.

Available Tools

Cloud SQL Admin Source Tools

Tool Name	Description
cloud-sql-list-databases	List Cloud SQL databases in an instance.
cloud-sql-list-instances	List Cloud SQL instances in a project.
cloud-sql-mysql-create-instance	Create a Cloud SQL for MySQL instance.
cloud-sql-clone-instance	Clone a Cloud SQL instance.
cloud-sql-create-backup	Creates a backup on a Cloud SQL instance.
cloud-sql-create-database	Create a new database in a Cloud SQL instance.
cloud-sql-create-users	Create a new user in a Cloud SQL instance.
cloud-sql-get-instance	Get a Cloud SQL instance resource.
cloud-sql-mssql-create-instance	Create a Cloud SQL for SQL Server instance.
cloud-sql-postgres-create-instance	Create a Cloud SQL for PostgreSQL instance.
cloud-sql-restore-backup	Restores a backup of a Cloud SQL instance.
cloud-sql-wait-for-operation	Wait for a long-running Cloud SQL operation to complete.
postgres-upgrade-precheck	Perform a pre-check for a Cloud SQL for PostgreSQL major version upgrade.

Example

kind: source
name: my-cloud-sql-admin
type: cloud-sql-admin
---
kind: source
name: my-oauth-cloud-sql-admin
type: cloud-sql-admin
useClientOAuth: true

Reference

field	type	required	description
type	string	true	Must be “cloud-sql-admin”.
defaultProject	string	false	The Google Cloud project ID to use for Cloud SQL infrastructure tools.
useClientOAuth	boolean	false	If true, the source will use client-side OAuth for authorization. Otherwise, it will use Application Default Credentials. Defaults to `false`.

Cloud SQL for SQL Server Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Cloud SQL for SQL Server is a managed database service that helps you set up, maintain, manage, and administer your SQL Server databases on Google Cloud.

If you are new to Cloud SQL for SQL Server, you can try creating and connecting to a database by following these instructions.

Available Tools

Cloud SQL for SQL Server Source Tools

Cloud SQL for SQL Server Source maintains full compatibility with SQL Server, allowing you to use the following tools with this connection:

Cloud SQL for MySQL Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Cloud SQL for MySQL is a fully-managed database service that helps you set up, maintain, manage, and administer your MySQL relational databases on Google Cloud Platform.

If you are new to Cloud SQL for MySQL, you can try creating and connecting to a database by following these instructions.

Available Tools

Cloud SQL for MySQL Source Tools

Cloud SQL for MySQL Source maintains full compatibility with MySQL, allowing you to use the following tools with this connection:

Cloud SQL for PostgreSQL Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Cloud SQL for PostgreSQL is a fully-managed database service that helps you set up, maintain, manage, and administer your PostgreSQL relational databases on Google Cloud Platform.

If you are new to Cloud SQL for PostgreSQL, you can try creating and connecting to a database by following these instructions.

Available Tools

Cloud SQL for PostgreSQL Source Tools

Cloud SQL for PostgreSQL Source maintains full compatibility with PostgreSQL, allowing you to use the following tools with this connection:

Gemini Data Analytics Source

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-gemini-data-analytics source provides a client to interact with the Gemini Data Analytics API. This allows tools to send natural language queries to the API.

Authentication can be handled in two ways:

Application Default Credentials (ADC) (Recommended): By default, the source uses ADC to authenticate with the API. The Toolbox server will fetch the credentials from its running environment (server-side authentication). This is the recommended method.
Client-side OAuth: If useClientOAuth is set to true, the source expects the authentication token to be provided by the caller when making a request to the Toolbox server (typically via an HTTP Bearer token). The Toolbox server will then forward this token to the underlying Gemini Data Analytics API calls.

Available Tools

Gemini Data Analytics Source Tools

Tool Name	Description
cloud-gemini-data-analytics-query	A tool to convert natural language queries into SQL statements using the Gemini Data Analytics QueryData API.

Example

kind: source
name: my-gda-source
type: cloud-gemini-data-analytics
projectId: my-project-id
---
kind: source
name: my-oauth-gda-source
type: cloud-gemini-data-analytics
projectId: my-project-id
useClientOAuth: true

Reference

field	type	required	description
type	string	true	Must be “cloud-gemini-data-analytics”.
projectId	string	true	The Google Cloud Project ID where the API is enabled.
useClientOAuth	boolean	false	If true, the source uses the token provided by the caller (forwarded to the API). Otherwise, it uses server-side Application Default Credentials (ADC). Defaults to `false`.

Cloud Healthcare API Source

Mon, 01 Jan 0001 00:00:00 +0000

About

The Cloud Healthcare API provides a managed solution for storing and accessing healthcare data in Google Cloud, providing a critical bridge between existing care systems and applications hosted on Google Cloud. It supports healthcare data standards such as HL7® FHIR®, HL7® v2, and DICOM®. It provides a fully managed, highly scalable, enterprise-grade development environment for building clinical and analytics solutions securely on Google Cloud.

A dataset is a container in your Google Cloud project that holds modality-specific healthcare data. Datasets contain other data stores, such as FHIR stores and DICOM stores, which in turn hold their own types of healthcare data.

Cloud Logging Admin Source

Mon, 01 Jan 0001 00:00:00 +0000

About

The Cloud Logging Admin source provides a client to interact with the Google Cloud Logging API. This allows tools to list log names, monitored resource types, and query log entries.

Authentication can be handled in two ways:

Application Default Credentials (ADC): By default, the source uses ADC to authenticate with the API.
Client-side OAuth: If useClientOAuth is set to true, the source will expect an OAuth 2.0 access token to be provided by the client (e.g., a web browser) for each request.

Available Tools

Cloud Logging Admin Source Tools

Tool Name	Description
cloud-logging-admin-list-log-names	A "cloud-logging-admin-list-log-names" tool lists the log names in the project.
cloud-logging-admin-list-resource-types	A "cloud-logging-admin-list-resource-types" tool lists the monitored resource types.
cloud-logging-admin-query-logs	A "cloud-logging-admin-query-logs" tool queries log entries.

Example

Initialize a Cloud Logging Admin source that uses ADC:

Cloud Monitoring Source

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-monitoring source provides a client to interact with the Google Cloud Monitoring API. This allows tools to access cloud monitoring metrics explorer and run promql queries.

Authentication can be handled in two ways:

Application Default Credentials (ADC): By default, the source uses ADC to authenticate with the API.
Client-side OAuth: If useClientOAuth is set to true, the source will expect an OAuth 2.0 access token to be provided by the client (e.g., a web browser) for each request.

Available Tools

Cloud Monitoring Source Tools

Tool Name	Description
cloud-monitoring-query-prometheus	The "cloud-monitoring-query-prometheus" tool fetches time series metrics for a project using a given prometheus query.

Example

kind: source
name: my-cloud-monitoring
type: cloud-monitoring
---
kind: source
name: my-oauth-cloud-monitoring
type: cloud-monitoring
useClientOAuth: true

Reference

field	type	required	description
type	string	true	Must be “cloud-monitoring”.
useClientOAuth	boolean	false	If true, the source will use client-side OAuth for authorization. Otherwise, it will use Application Default Credentials. Defaults to `false`.

CockroachDB Source

Mon, 01 Jan 0001 00:00:00 +0000

About

CockroachDB is a distributed SQL database designed for cloud-native applications. It provides strong consistency, horizontal scalability, and built-in resilience with automatic failover and recovery. CockroachDB uses the PostgreSQL wire protocol, making it compatible with many PostgreSQL tools and drivers while providing unique features like multi-region deployments and distributed transactions.

Minimum Version: CockroachDB v25.1 or later is recommended for full tool compatibility.

Available Tools

CockroachDB Source Tools

Tool Name	Description
cockroachdb-execute-sql	Execute ad-hoc SQL statements against a CockroachDB database.
cockroachdb-list-schemas	List schemas in a CockroachDB database.
cockroachdb-list-tables	List tables in a CockroachDB database with schema details.
cockroachdb-sql	Execute parameterized SQL queries in CockroachDB.

Requirements

Database User

This source uses standard authentication. You will need to create a CockroachDB user to login to the database with. For CockroachDB Cloud deployments, SSL/TLS is required.

Couchbase Source

Mon, 01 Jan 0001 00:00:00 +0000

About

A couchbase source establishes a connection to a Couchbase database cluster, allowing tools to execute SQL queries against it.

Available Tools

Couchbase Source Tools

Tool Name	Description
couchbase-sql	A "couchbase-sql" tool executes a pre-defined SQL statement against a Couchbase database.

Example

kind: source
name: my-couchbase-instance
type: couchbase
connectionString: couchbase://localhost
bucket: travel-sample
scope: inventory
username: Administrator
password: password

Note

Dataplex Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Dataplex Universal Catalog is a unified, intelligent governance solution for data and AI assets in Google Cloud. Dataplex Universal Catalog powers AI, analytics, and business intelligence at scale.

At the heart of these governance capabilities is a catalog that contains a centralized inventory of the data assets in your organization. Dataplex Universal Catalog holds business, technical, and runtime metadata for all of your data. It helps you discover relationships and semantics in the metadata by applying artificial intelligence and machine learning.

Dataproc Clusters Source

Mon, 01 Jan 0001 00:00:00 +0000

About

The Dataproc Clusters source allows Toolbox to interact with Dataproc Clusters hosted on Google Cloud.

Available Tools

Dataproc Clusters Source Tools

Tool Name	Description
dataproc-get-cluster	A "dataproc-get-cluster" tool retrieves a specific Dataproc cluster from the source.
dataproc-get-job	A "dataproc-get-job" tool retrieves a specific Dataproc job from the source.
dataproc-list-clusters	A "dataproc-list-clusters" tool returns a list of Dataproc clusters from the source.
dataproc-list-jobs	A "dataproc-list-jobs" tool returns a list of Dataproc jobs from the source.

Requirements

IAM Permissions

Dataproc uses Identity and Access Management (IAM) to control user and group access to Dataproc resources.

Dgraph Source

Mon, 01 Jan 0001 00:00:00 +0000

Note

Elasticsearch Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Elasticsearch is a distributed, free and open search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured.

If you are new to Elasticsearch, you can learn how to set up a cluster and start indexing data.

Elasticsearch uses ES|QL for querying data. ES|QL is a powerful query language that allows you to search and aggregate data in Elasticsearch.

See the official documentation for more information.

Available Tools

Elasticsearch Source Tools

Tool Name	Description
elasticsearch-esql	Execute ES\|QL queries.

Requirements

API Key

Toolbox uses an API key to authorize and authenticate when interacting with Elasticsearch.

Firebird Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Firebird is a relational database management system offering many ANSI SQL standard features that runs on Linux, Windows, and a variety of Unix platforms. It is known for its small footprint, powerful features, and easy maintenance.

Available Tools

Firebird Source Tools

Tool Name	Description
firebird-execute-sql	A "firebird-execute-sql" tool executes a SQL statement against a Firebird database.
firebird-sql	A "firebird-sql" tool executes a pre-defined SQL statement against a Firebird database.

Requirements

Database User

This source uses standard authentication. You will need to create a Firebird user to login to the database with.

Firestore Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Firestore is a NoSQL document database built for automatic scaling, high performance, and ease of application development. While the Firestore interface has many of the same features as traditional databases, as a NoSQL database it differs from them in the way it describes relationships between data objects.

If you are new to Firestore, you can create a database and learn the basics.

Available Tools

Firestore Source Tools

Tool Name	Description
firestore-add-documents	A "firestore-add-documents" tool adds document to a given collection path.
firestore-delete-documents	A "firestore-delete-documents" tool deletes multiple documents from Firestore by their paths.
firestore-get-documents	A "firestore-get-documents" tool retrieves multiple documents from Firestore by their paths.
firestore-get-rules	A "firestore-get-rules" tool retrieves the active Firestore security rules for the current project.
firestore-list-collections	A "firestore-list-collections" tool lists collections in Firestore, either at the root level or as subcollections of a document.
firestore-query	Query a Firestore collection with parameterizable filters and Firestore native JSON value types
firestore-query-collection	A "firestore-query-collection" tool allow to query collections in Firestore.
firestore-update-document	A "firestore-update-document" tool updates an existing document in Firestore.
firestore-validate-rules	A "firestore-validate-rules" tool validates Firestore security rules syntax and semantic correctness without deploying them. It provides detailed error reporting with source positions and code snippets.

Requirements

IAM Permissions

Firestore uses Identity and Access Management (IAM) to control user and group access to Firestore resources. Toolbox will use your Application Default Credentials (ADC) to authorize and authenticate when interacting with Firestore.

HTTP Source

Mon, 01 Jan 0001 00:00:00 +0000

About

The HTTP Source allows Toolbox to retrieve data from arbitrary HTTP endpoints. This enables Generative AI applications to access data from web APIs and other HTTP-accessible resources.

Available Tools

HTTP Source Tools

Tool Name	Description
http	A "http" tool sends out an HTTP request to an HTTP endpoint.

Example

kind: source
name: my-http-source
type: http
baseUrl: https://api.example.com/data
timeout: 10s # default to 30s
headers:
 Authorization: Bearer ${API_KEY}
 Content-Type: application/json
queryParams:
 param1: value1
 param2: value2
# returnFullError: false
# disableSslVerification: false

Tip

Looker Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Looker is a web based business intelligence and data management tool that provides a semantic layer to facilitate querying. It can be deployed in the cloud, on GCP, or on premises.

Available Tools

Looker Source Tools

Tool Name	Description
looker-add-dashboard-element	"looker-add-dashboard-element" creates a dashboard element in the given dashboard.
looker-add-dashboard-filter	The "looker-add-dashboard-filter" tool adds a filter to a specified dashboard.
looker-conversational-analytics	The "looker-conversational-analytics" tool will use the Conversational Analaytics API to analyze data from Looker
looker-create-project-directory	A "looker-create-project-directory" tool creates a new directory in a LookML project.
looker-create-project-file	A "looker-create-project-file" tool creates a new LookML file in a project.
looker-delete-project-directory	A "looker-delete-project-directory" tool deletes a directory from a LookML project.
looker-delete-project-file	A "looker-delete-project-file" tool deletes a LookML file in a project.
looker-dev-mode	A "looker-dev-mode" tool changes the current session into and out of dev mode
looker-generate-embed-url	"looker-generate-embed-url" generates an embeddable URL for Looker content.
looker-get-connection-databases	A "looker-get-connection-databases" tool returns all the databases in a connection.
looker-get-connection-schemas	A "looker-get-connection-schemas" tool returns all the schemas in a connection.
looker-get-connection-table-columns	A "looker-get-connection-table-columns" tool returns all the columns for each table specified.
looker-get-connection-tables	A "looker-get-connection-tables" tool returns all the tables in a connection.
looker-get-connections	A "looker-get-connections" tool returns all the connections in the source.
looker-get-dashboards	"looker-get-dashboards" tool searches for a saved Dashboard by name or description.
looker-get-dimensions	A "looker-get-dimensions" tool returns all the dimensions from a given explore in a given model in the source.
looker-get-explores	A "looker-get-explores" tool returns all explores for the given model from the source.
looker-get-filters	A "looker-get-filters" tool returns all the filters from a given explore in a given model in the source.
looker-get-looks	"looker-get-looks" searches for saved Looks in a Looker source.
looker-get-measures	A "looker-get-measures" tool returns all the measures from a given explore in a given model in the source.
looker-get-models	A "looker-get-models" tool returns all the models in the source.
looker-get-parameters	A "looker-get-parameters" tool returns all the parameters from a given explore in a given model in the source.
looker-get-project-directories	A "looker-get-project-directories" tool returns the directories within a specific LookML project.
looker-get-project-file	A "looker-get-project-file" tool returns the contents of a LookML fle.
looker-get-project-files	A "looker-get-project-files" tool returns all the LookML fles in a project in the source.
looker-get-projects	A "looker-get-projects" tool returns all the LookML projects in the source.
looker-git-branch	A "looker-git-branch" tool is used to retrieve and manipulate the git branch of a LookML project.
looker-health-analyze	"looker-health-analyze" provides a set of analytical commands for a Looker instance, allowing users to analyze projects, models, and explores.
looker-health-pulse	"looker-health-pulse" performs health checks on a Looker instance, with multiple actions available (e.g., checking database connections, dashboard performance, etc).
looker-health-vacuum	"looker-health-vacuum" provides a set of commands to audit and identify unused LookML objects in a Looker instance.
looker-make-dashboard	"looker-make-dashboard" generates a Looker dashboard in the users personal folder in Looker
looker-make-look	"looker-make-look" generates a Looker look in the users personal folder in Looker
looker-query	"looker-query" runs an inline query using the Looker semantic model.
looker-query-sql	"looker-query-sql" generates a sql query using the Looker semantic model.
looker-query-url	"looker-query-url" generates a url link to a Looker explore.
looker-run-dashboard	"looker-run-dashboard" runs the queries associated with a dashboard.
looker-run-look	"looker-run-look" runs the query associated with a saved Look.
looker-update-project-file	A "looker-update-project-file" tool updates the content of a LookML file in a project.
looker-validate-project	A "looker-validate-project" tool checks the syntax of a LookML project and reports any errors

Requirements

Looker User

This source only uses API authentication. You will need to create an API user to login to Looker.

MariaDB Source

Mon, 01 Jan 0001 00:00:00 +0000

About

MariaDB is a relational database management system derived from MySQL. It implements the MySQL protocol and client libraries and supports modern SQL features with a focus on performance and reliability.

Note: MariaDB is supported using the MySQL source.

Available Tools

MariaDB Source Tools

MariaDB Source maintains full compatibility with MySQL, allowing you to use the following tools with this connection:

Tool Name	Description
mysql-execute-sql	A "mysql-execute-sql" tool executes a SQL statement against a MySQL database.
mysql-get-query-plan	A "mysql-get-query-plan" tool gets the execution plan for a SQL statement against a MySQL database.
mysql-list-active-queries	A "mysql-list-active-queries" tool lists active queries in a MySQL database.
mysql-list-table-fragmentation	A "mysql-list-table-fragmentation" tool lists top N fragemented tables in MySQL.
mysql-list-tables	The "mysql-list-tables" tool lists schema information for all or specified tables in a MySQL database.
mysql-list-tables-missing-unique-indexes	A "mysql-list-tables-missing-unique-indexes" tool lists tables that do not have primary or unique indices in a MySQL instance.
mysql-sql	A "mysql-sql" tool executes a pre-defined SQL statement against a MySQL database.

Requirements

Database User

This source only uses standard authentication. You will need to create a MariaDB user to log in to the database.

MindsDB Source

Mon, 01 Jan 0001 00:00:00 +0000

About

MindsDB is an AI federated database in the world. It allows you to combine information from hundreds of datasources as if they were SQL, supporting joins across datasources and enabling you to query all unstructured data as if it were structured.

MindsDB translates MySQL queries into whatever API is needed - whether it’s REST APIs, GraphQL, or native database protocols. This means you can write standard SQL queries and MindsDB automatically handles the translation to APIs like Salesforce, Jira, GitHub, email systems, MongoDB, and hundreds of other datasources.

MongoDB Source

Mon, 01 Jan 0001 00:00:00 +0000

About

MongoDB is a popular NoSQL database that stores data in flexible, JSON-like documents, making it easy to develop and scale applications.

Available Tools

MongoDB Source Tools

Tool Name	Description
mongodb-aggregate	A "mongodb-aggregate" tool executes a multi-stage aggregation pipeline against a MongoDB collection.
mongodb-delete-many	A "mongodb-delete-many" tool deletes all documents from a MongoDB collection that match a filter.
mongodb-delete-one	A "mongodb-delete-one" tool deletes a single document from a MongoDB collection.
mongodb-find	A "mongodb-find" tool finds and retrieves documents from a MongoDB collection.
mongodb-find-one	A "mongodb-find-one" tool finds and retrieves a single document from a MongoDB collection.
mongodb-insert-many	A "mongodb-insert-many" tool inserts multiple new documents into a MongoDB collection.
mongodb-insert-one	A "mongodb-insert-one" tool inserts a single new document into a MongoDB collection.
mongodb-update-many	A "mongodb-update-many" tool updates all documents in a MongoDB collection that match a filter.
mongodb-update-one	A "mongodb-update-one" tool updates a single document in a MongoDB collection.

Example

kind: source
name: my-mongodb
type: mongodb
uri: "mongodb+srv://username:password@host.mongodb.net"

Reference

field	type	required	description
type	string	true	Must be “mongodb”.
uri	string	true	connection string to connect to MongoDB

SQL Server Source

Mon, 01 Jan 0001 00:00:00 +0000

About

SQL Server is a relational database management system (RDBMS) developed by Microsoft that allows users to store, retrieve, and manage large amount of data through a structured format.

Available Tools

SQL Server Source Tools

Tool Name	Description
mssql-execute-sql	A "mssql-execute-sql" tool executes a SQL statement against a SQL Server database.
mssql-list-tables	The "mssql-list-tables" tool lists schema information for all or specified tables in a SQL server database.
mssql-sql	A "mssql-sql" tool executes a pre-defined SQL statement against a SQL Server database.

Requirements

Database User

This source only uses standard authentication. You will need to create a SQL Server user to login to the database with.

MySQL Source

Mon, 01 Jan 0001 00:00:00 +0000

About

MySQL is a relational database management system (RDBMS) that stores and manages data. It’s a popular choice for developers because of its reliability, performance, and ease of use.

Available Tools

MySQL Source Tools

Tool Name	Description
mysql-execute-sql	A "mysql-execute-sql" tool executes a SQL statement against a MySQL database.
mysql-get-query-plan	A "mysql-get-query-plan" tool gets the execution plan for a SQL statement against a MySQL database.
mysql-list-active-queries	A "mysql-list-active-queries" tool lists active queries in a MySQL database.
mysql-list-table-fragmentation	A "mysql-list-table-fragmentation" tool lists top N fragemented tables in MySQL.
mysql-list-tables	The "mysql-list-tables" tool lists schema information for all or specified tables in a MySQL database.
mysql-list-tables-missing-unique-indexes	A "mysql-list-tables-missing-unique-indexes" tool lists tables that do not have primary or unique indices in a MySQL instance.
mysql-sql	A "mysql-sql" tool executes a pre-defined SQL statement against a MySQL database.

Requirements

Database User

This source only uses standard authentication. You will need to create a MySQL user to login to the database with.

Neo4j Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Neo4j is a powerful, open source graph database system with over 15 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance.

Available Tools

Neo4j Source Tools

Tool Name	Description
neo4j-cypher	A "neo4j-cypher" tool executes a pre-defined cypher statement against a Neo4j database.
neo4j-execute-cypher	A "neo4j-execute-cypher" tool executes any arbitrary Cypher statement against a Neo4j database.
neo4j-schema	A "neo4j-schema" tool extracts a comprehensive schema from a Neo4j database.

Requirements

Database User

This source only uses standard authentication. You will need to create a Neo4j user to log in to the database with, or use the default neo4j user if available.

OceanBase Source

Mon, 01 Jan 0001 00:00:00 +0000

About

OceanBase is a distributed relational database management system (RDBMS) that provides high availability, scalability, and strong consistency. It’s designed to handle large-scale data processing and is compatible with MySQL, making it easy for developers to migrate from MySQL to OceanBase.

Features

MySQL Compatibility

OceanBase is highly compatible with MySQL, supporting most MySQL SQL syntax, data types, and functions. This makes it easy to migrate existing MySQL applications to OceanBase.

Oracle Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Oracle Database is a multi-model database management system produced and marketed by Oracle Corporation. It is commonly used for running online transaction processing (OLTP), data warehousing (DW), and mixed (OLTP & DW) database workloads.

Available Tools

Oracle Source Tools

Tool Name	Description
list_tables	Lists all tables in the current user's schema
oracle-execute-sql	An "oracle-execute-sql" tool executes a SQL statement against an Oracle database.
oracle-sql	An "oracle-sql" tool executes a pre-defined SQL statement against an Oracle database.

Requirements

Database User

This source uses standard authentication. You will need to create an Oracle user to log in to the database with the necessary permissions.

PostgreSQL Source

Mon, 01 Jan 0001 00:00:00 +0000

About

PostgreSQL is a powerful, open source object-relational database system with over 35 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance.

Available Tools

PostgreSQL Source Tools

Tool Name	Description
postgres-database-overview	The "postgres-database-overview" fetches the current state of the PostgreSQL server.
postgres-execute-sql	A "postgres-execute-sql" tool executes a SQL statement against a Postgres database.
postgres-get-column-cardinality	The "postgres-get-column-cardinality" tool estimates the number of unique values in one or all columns of a Postgres database table.
postgres-list-active-queries	The "postgres-list-active-queries" tool lists currently active queries in a Postgres database.
postgres-list-available-extensions	The "postgres-list-available-extensions" tool retrieves all PostgreSQL extensions available for installation on a Postgres database.
postgres-list-database-stats	The "postgres-list-database-stats" tool lists lists key performance and activity statistics of PostgreSQL databases.
postgres-list-indexes	The "postgres-list-indexes" tool lists indexes in a Postgres database.
postgres-list-installed-extensions	The "postgres-list-installed-extensions" tool retrieves all PostgreSQL extensions installed on a Postgres database.
postgres-list-locks	The "postgres-list-locks" tool lists active locks in the database, including the associated process, lock type, relation, mode, and the query holding or waiting on the lock.
postgres-list-pg-settings	The "postgres-list-pg-settings" tool lists PostgreSQL run-time configuration settings.
postgres-list-publication-tables	The "postgres-list-publication-tables" tool lists publication tables in a Postgres database.
postgres-list-query-stats	The "postgres-list-query-stats" tool lists query statistics from a Postgres database.
postgres-list-roles	The "postgres-list-roles" tool lists user-created roles in a Postgres database.
postgres-list-schemas	The "postgres-list-schemas" tool lists user-defined schemas in a database.
postgres-list-sequences	The "postgres-list-sequences" tool lists sequences in a Postgres database.
postgres-list-stored-procedure	The "postgres-list-stored-procedure" tool retrieves metadata for stored procedures in PostgreSQL, including procedure definitions, owners, languages, and descriptions.
postgres-list-table-stats	The "postgres-list-table-stats" tool reports table statistics including size, scan metrics, and bloat indicators for PostgreSQL tables.
postgres-list-tables	The "postgres-list-tables" tool lists schema information for all or specified tables in a Postgres database.
postgres-list-tablespaces	The "postgres-list-tablespaces" tool lists tablespaces in a Postgres database.
postgres-list-triggers	The "postgres-list-triggers" tool lists triggers in a Postgres database.
postgres-list-views	The "postgres-list-views" tool lists views in a Postgres database, with a default limit of 50 rows.
postgres-long-running-transactions	The postgres-long-running-transactions tool Identifies and lists database transactions that exceed a specified time limit. For each of the long running transactions, the output contains the process id, database name, user name, application name, client address, state, connection age, transaction age, query age, last activity age, wait event type, wait event, and query string.
postgres-replication-stats	The "postgres-replication-stats" tool reports replication-related metrics for WAL streaming replicas, including lag sizes presented in human-readable form.
postgres-sql	A "postgres-sql" tool executes a pre-defined SQL statement against a Postgres database.

Pre-built Configurations

PostgreSQL using MCP Connect your IDE to PostgreSQL using Toolbox.

Requirements

Database User

This source only uses standard authentication. You will need to create a PostgreSQL user to login to the database with.

Redis Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Redis is a in-memory data structure store, used as a database, cache, and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, and geospatial indexes with radius queries.

If you are new to Redis, you can find installation and getting started guides on the official Redis website.

Available Tools

Redis Source Tools

Tool Name	Description
redis	A "redis" tool executes a set of pre-defined Redis commands against a Redis instance.

Requirements

Example

Redis

AUTH string is a password for connection to Redis. If you have the requirepass directive set in your Redis configuration, incoming client connections must authenticate in order to connect.

Serverless for Apache Spark Source

Mon, 01 Jan 0001 00:00:00 +0000

About

The Serverless for Apache Spark source allows Toolbox to interact with Spark batches hosted on Google Cloud Serverless for Apache Spark.

Available Tools

Serverless for Apache Spark Source Tools

Tool Name	Description
serverless-spark-get-batch	A "serverless-spark-get-batch" tool gets a single Spark batch from the source.
serverless-spark-get-session-template	A "serverless-spark-get-session-template" tool retrieves a specific Spark session template from the source.
serverless-spark-list-batches	A "serverless-spark-list-batches" tool returns a list of Spark batches from the source.
serverless-spark-cancel-batch	A "serverless-spark-cancel-batch" tool cancels a running Spark batch operation.
serverless-spark-create-pyspark-batch	A "serverless-spark-create-pyspark-batch" tool submits a Spark batch to run asynchronously.
serverless-spark-create-spark-batch	A "serverless-spark-create-spark-batch" tool submits a Spark batch to run asynchronously.

Requirements

IAM Permissions

Serverless for Apache Spark uses Identity and Access Management (IAM) to control user and group access to serverless Spark resources like batches and sessions.

SingleStore Source

Mon, 01 Jan 0001 00:00:00 +0000

About

SingleStore is a distributed SQL database built to power intelligent applications. It is both relational and multi-model, enabling developers to easily build and scale applications and workloads.

SingleStore is built around Universal Storage which combines in-memory rowstore and on-disk columnstore data formats to deliver a single table type that is optimized to handle both transactional and analytical workloads.

Available Tools

SingleStore Source Tools

Tool Name	Description
singlestore-execute-sql	A "singlestore-execute-sql" tool executes a SQL statement against a SingleStore database.
singlestore-sql	A "singlestore-sql" tool executes a pre-defined SQL statement against a SingleStore database.

Requirements

Database User

This source only uses standard authentication. You will need to create a database user to login to the database with.

Snowflake Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Snowflake is a cloud data platform that provides a data warehouse-as-a-service designed for the cloud.

Available Tools

Snowflake Source Tools

Tool Name	Description
snowflake-execute-sql	A "snowflake-execute-sql" tool executes a SQL statement against a Snowflake database.
snowflake-sql	A "snowflake-sql" tool executes a pre-defined SQL statement against a Snowflake database.

Requirements

Database User

This source only uses standard authentication. You will need to create a Snowflake user to login to the database with.

Spanner Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Spanner is a fully managed, mission-critical database service that brings together relational, graph, key-value, and search. It offers transactional consistency at global scale, automatic, synchronous replication for high availability, and support for two SQL dialects: GoogleSQL (ANSI 2011 with extensions) and PostgreSQL.

If you are new to Spanner, you can try to create and query a database using the Google Cloud console.

Available Tools

Spanner Source Tools

Tool Name	Description
spanner-execute-sql	A "spanner-execute-sql" tool executes a SQL statement against a Spanner database.
spanner-sql	A "spanner-sql" tool executes a pre-defined SQL statement against a Google Cloud Spanner database.
spanner-list-graphs	A "spanner-list-graphs" tool retrieves schema information about graphs in a Google Cloud Spanner database.
spanner-list-tables	A "spanner-list-tables" tool retrieves schema information about tables in a Google Cloud Spanner database.

Pre-built Configurations

Spanner using MCP Connect your IDE to Spanner using Toolbox.

Requirements

IAM Permissions

Spanner uses Identity and Access Management (IAM) to control user and group access to Spanner resources at the project, Spanner instance, and Spanner database levels. Toolbox will use your Application Default Credentials (ADC) to authorize and authenticate when interacting with Spanner.

SQLite Source

Mon, 01 Jan 0001 00:00:00 +0000

About

SQLite is a software library that provides a relational database management system. The lite in SQLite means lightweight in terms of setup, database administration, and required resources.

SQLite has the following notable characteristics:

Self-contained with no external dependencies
Serverless - the SQLite library accesses its storage files directly
Single database file that can be easily copied or moved
Zero-configuration - no setup or administration needed
Transactional with ACID properties

Available Tools

SQLite Source Tools

Tool Name	Description
sqlite-execute-sql	A "sqlite-execute-sql" tool executes a single SQL statement against a SQLite database.
sqlite-sql	Execute SQL statements against a SQLite database.

Pre-built Configurations

SQLite using MCP Connect your IDE to SQlite using Toolbox.

Requirements

Database File

You need a SQLite database file. This can be:

TiDB Source

Mon, 01 Jan 0001 00:00:00 +0000

About

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL-compatible and features horizontal scalability, strong consistency, and high availability.

Available Tools

TiDB Source Tools

Tool Name	Description
tidb-execute-sql	A "tidb-execute-sql" tool executes a SQL statement against a TiDB database.
tidb-sql	A "tidb-sql" tool executes a pre-defined SQL statement against a TiDB database.

Requirements

Database User

This source uses standard MySQL protocol authentication. You will need to create a TiDB user to login to the database with.

Trino Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Trino is a distributed SQL query engine designed for fast analytic queries against data of any size. It allows you to query data where it lives, including Hive, Cassandra, relational databases or even proprietary data stores.

Available Tools

Trino Source Tools

Tool Name	Description
trino-execute-sql	A "trino-execute-sql" tool executes a SQL statement against a Trino database.
trino-sql	A "trino-sql" tool executes a pre-defined SQL statement against a Trino database.

Requirements

Trino Cluster

You need access to a running Trino cluster with appropriate user permissions for the catalogs and schemas you want to query.

Valkey Source

Mon, 01 Jan 0001 00:00:00 +0000

About

Valkey is an open-source, in-memory data structure store that originated as a fork of Redis. It’s designed to be used as a database, cache, and message broker, supporting a wide range of data structures like strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, and geospatial indexes with radius queries.

If you’re new to Valkey, you can find installation and getting started guides on the official Valkey website.

YugabyteDB Source

Mon, 01 Jan 0001 00:00:00 +0000

About

YugabyteDB is a high-performance, distributed SQL database designed for global, internet-scale applications, with full PostgreSQL compatibility.

Available Tools

YugabyteDB Source Tools

Tool Name	Description
yugabytedb-sql	A "yugabytedb-sql" tool executes a pre-defined SQL statement against a YugabyteDB database.

Example

kind: source
name: my-yb-source
type: yugabytedb
host: 127.0.0.1
port: 5433
database: yugabyte
user: ${USER_NAME}
password: ${PASSWORD}
loadBalance: true
topologyKeys: cloud.region.zone1:1,cloud.region.zone2:2

Reference

field	type	required	description
type	string	true	Must be “yugabytedb”.
host	string	true	IP address to connect to.
port	integer	true	Port to connect to. The default port is 5433.
database	string	true	Name of the YugabyteDB database to connect to. The default database name is yugabyte.
user	string	true	Name of the YugabyteDB user to connect as. The default user is yugabyte.
password	string	true	Password of the YugabyteDB user. The default password is yugabyte.
loadBalance	boolean	false	If true, enable uniform load balancing. The default loadBalance value is false.
topologyKeys	string	false	Comma-separated geo-locations in the form cloud.region.zone:priority to enable topology-aware load balancing. Ignored if loadBalance is false. It is null by default.
ybServersRefreshInterval	integer	false	The interval (in seconds) to refresh the servers list; ignored if loadBalance is false. The default value of ybServersRefreshInterval is 300.
fallbackToTopologyKeysOnly	boolean	false	If set to true and topologyKeys are specified, only connect to nodes specified in topologyKeys. By defualt, this is set to false.
failedHostReconnectDelaySecs	integer	false	Time (in seconds) to wait before trying to connect to failed nodes. The default value of is 5.

spanner-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A spanner-execute-sql tool executes a SQL statement against a Spanner database.

spanner-execute-sql takes one input parameter sql and run the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Spanner

Example

kind: tool
name: execute_sql_tool
type: spanner-execute-sql
source: my-spanner-instance
description: Use this tool to execute sql statement.

Reference

field	type	required	description
type	string	true	Must be “spanner-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.
readOnly	bool	false	When set to `true`, the `statement` is run as a read-only transaction. Default: `false`.

spanner-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A spanner-sql tool executes a pre-defined SQL statement (either googlesql or postgresql) against a Cloud Spanner database.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Spanner

GoogleSQL

For the googlesql dialect, the specified SQL statement is executed as a data manipulation language (DML) statements, and specified parameters will inserted according to their name: e.g. @name.

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

sqlite-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A sqlite-execute-sql tool executes a single SQL statement against a SQLite database.

This tool is designed for direct execution of SQL statements. It takes a single sql input parameter and runs the SQL statement against the configured SQLite source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

sqlite-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A sqlite-sql tool executes SQL statements against a SQLite database.

SQLite uses the ? placeholder for parameters in SQL statements. Parameters are bound in the order they are provided.

The statement field supports any valid SQLite SQL statement, including SELECT, INSERT, UPDATE, DELETE, CREATE/ALTER/DROP table statements, and other DDL statements.

Compatible Sources

This tool can be used with the following database sources:

Source Name
SQLite

Example

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

tidb-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A tidb-execute-sql tool executes a SQL statement against a TiDB database.

tidb-execute-sql takes one input parameter sql and run the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
TiDB

Example

kind: tool
name: execute_sql_tool
type: tidb-execute-sql
source: my-tidb-instance
description: Use this tool to execute sql statement.

Reference

field	type	required	description
type	string	true	Must be “tidb-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

tidb-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A tidb-sql tool executes a pre-defined SQL statement against a TiDB database.

The specified SQL statement is executed as a prepared statement, and expects parameters in the SQL query to be in the form of placeholders ?.

Compatible Sources

This tool can be used with the following database sources:

Source Name
TiDB

Example

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

trino-execute-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A trino-execute-sql tool executes a SQL statement against a Trino database.

trino-execute-sql takes one input parameter sql and run the sql statement against the source.

Note: This tool is intended for developer assistant workflows with human-in-the-loop and shouldn’t be used for production agents.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Trino

Example

kind: tool
name: execute_sql_tool
type: trino-execute-sql
source: my-trino-instance
description: Use this tool to execute sql statement.

Reference

field	type	required	description
type	string	true	Must be “trino-execute-sql”.
source	string	true	Name of the source the SQL should execute on.
description	string	true	Description of the tool that is passed to the LLM.

trino-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A trino-sql tool executes a pre-defined SQL statement against a Trino database. The specified SQL statement is executed as a prepared statement, and expects parameters in the SQL query to be in the form of placeholders ?.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Trino

Example

Note: This tool uses parameterized queries to prevent SQL injections. Query parameters can be used as substitutes for arbitrary expressions. Parameters cannot be used as substitutes for identifiers, column names, table names, or other parts of the query.

valkey

Mon, 01 Jan 0001 00:00:00 +0000

About

A valkey tool executes a series of pre-defined Valkey commands against a Valkey instance.

The specified Valkey commands are executed sequentially. Each command is represented as a string array, where the first element is the command name (e.g., SET, GET, HGETALL) and subsequent elements are its arguments.

Dynamic Command Parameters

Command arguments can be templated using the $variableName annotation. The array type parameters will be expanded once into multiple arguments. Take the following config for example:

wait

Mon, 01 Jan 0001 00:00:00 +0000

About

A wait tool pauses execution for a specified duration. This can be useful in workflows where a delay is needed between steps.

wait takes one input parameter duration which is a string representing the time to wait (e.g., “10s”, “2m”, “1h”).

Info

yugabytedb-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A yugabytedb-sql tool executes a pre-defined SQL statement against a YugabyteDB database.

The specified SQL statement is executed as a prepared statement, and specified parameters will inserted according to their position: e.g. 1 will be the first parameter specified, $@ will be the second parameter, and so on. If template parameters are included, they will be resolved before execution of the prepared statement.

Compatible Sources

This tool can be used with the following database sources:

AlloyDB Admin API using MCP

Mon, 01 Jan 0001 00:00:00 +0000

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AlloyDB using MCP

Mon, 01 Jan 0001 00:00:00 +0000

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alloydb-create-user

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-create-user tool creates a new database user (ALLOYDB_BUILT_IN or ALLOYDB_IAM_USER) within a specified cluster.

Permissions & APIs Required: Before using, ensure the following on your GCP project:

The AlloyDB API is enabled.
The user or service account executing the tool has one of the following IAM roles:
- roles/alloydb.admin (the AlloyDB Admin predefined IAM role)
- roles/owner (the Owner basic IAM role)
- roles/editor (the Editor basic IAM role)

The tool takes the following input parameters:

BigQuery using MCP

Mon, 01 Jan 0001 00:00:00 +0000

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clickhouse-sql

Mon, 01 Jan 0001 00:00:00 +0000

About

A clickhouse-sql tool executes SQL queries as prepared statements against a ClickHouse database.

This tool supports both template parameters (for SQL statement customization) and regular parameters (for prepared statement values), providing flexible query execution capabilities.

Compatible Sources

This tool can be used with the following database sources:

Source Name
ClickHouse

Example

kind: tool
name: my_analytics_query
type: clickhouse-sql
source: my-clickhouse-instance
description: Get user analytics for a specific date range
statement: |
 SELECT 
 user_id,
 count(*) as event_count,
 max(timestamp) as last_event
 FROM events 
 WHERE date >= ? AND date <= ?
 GROUP BY user_id
 ORDER BY event_count DESC
 LIMIT ?
parameters:
 - name: start_date
 description: Start date for the query (YYYY-MM-DD format)
 - name: end_date 
 description: End date for the query (YYYY-MM-DD format)
 - name: limit
 description: Maximum number of results to return

Template Parameters Example

kind: tool
name: flexible_table_query
type: clickhouse-sql
source: my-clickhouse-instance
description: Query any table with flexible columns
statement: |
 SELECT {{columns}}
 FROM {{table_name}}
 WHERE created_date >= ?
 LIMIT ?
templateParameters:
 - name: columns
 description: Comma-separated list of columns to select
 - name: table_name
 description: Name of the table to query
parameters:
 - name: start_date
 description: Start date filter
 - name: limit
 description: Maximum number of results

Reference

field	type	required	description
type	string	true	Must be “clickhouse-sql”.
source	string	true	Name of the ClickHouse source to execute SQL against.
description	string	true	Description of the tool that is passed to the LLM.
statement	string	true	The SQL statement template to execute.
parameters	array of Parameter	false	Parameters for prepared statement values.
templateParameters	array of Parameter	false	Parameters for SQL statement template customization.

Cloud SQL for MySQL using MCP

Mon, 01 Jan 0001 00:00:00 +0000

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Cloud SQL for Postgres using MCP

Mon, 01 Jan 0001 00:00:00 +0000

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Cloud SQL for SQL Server using MCP

Mon, 01 Jan 0001 00:00:00 +0000

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cloud-sql-mysql-create-instance

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-mysql-create-instance tool creates a new Cloud SQL for MySQL instance in a specified Google Cloud project.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Parameters

The cloud-sql-mysql-create-instance tool has the following parameters:

field	type	required	description
project	string	true	The Google Cloud project ID.
name	string	true	The name of the instance to create.
databaseVersion	string	false	The database version for MySQL. If not specified, defaults to the latest available version (e.g., `MYSQL_8_4`).
rootPassword	string	true	The root password for the instance.
editionPreset	string	false	The edition of the instance. Can be `Production` or `Development`. Defaults to `Development`.

Example

Here is an example of how to configure the cloud-sql-mysql-create-instance tool in your tools.yaml file:

Core

Mon, 01 Jan 0001 00:00:00 +0000

Overview

The package provides a java interface to the MCP Toolbox service, enabling you to load and invoke tools from your own applications.

Installation

This SDK is distributed via a Maven Central Repository.

Maven

Add the dependency to your pom.xml:

<dependency>
 <groupId>com.google.cloud.mcp</groupId>
 <artifactId>mcp-toolbox-sdk-java</artifactId>
 <!-- Replace 'VERSION' with the latest version from https://mvnrepository.com/artifact/com.google.cloud.mcp/mcp-toolbox-sdk-java -->
 <version>VERSION</version>
 <scope>compile</scope>
</dependency>

Gradle

dependencies {
 // Replace 'VERSION' with the latest version from https://mvnrepository.com/artifact/com.google.cloud.mcp/mcp-toolbox-sdk-java
 implementation("com.google.cloud.mcp:mcp-toolbox-sdk-java:VERSION") 
}

Quickstart

Here is the minimal code needed to connect to a MCP Toolbox and invoke a tool.

Core

Mon, 01 Jan 0001 00:00:00 +0000

Overview

The @toolbox-sdk/core package provides a Javascript interface to the MCP Toolbox service, enabling you to load and invoke tools from your own applications.

Supported Environments

This SDK is a standard Node.js package built with TypeScript, ensuring broad compatibility with the modern JavaScript ecosystem.

Node.js: Actively supported on Node.js v18.x and higher. The package is compatible with both modern ES Module (import) and legacy CommonJS (require).
TypeScript: The SDK is written in TypeScript and ships with its own type declarations, providing a first-class development experience with autocompletion and type-checking out of the box.
JavaScript: Fully supports modern JavaScript in Node.js environments.

Installation

npm install @toolbox-sdk/core

Quickstart

Start the Toolbox Service

Core

Mon, 01 Jan 0001 00:00:00 +0000

Overview

The toolbox-core package provides a Python interface to the MCP Toolbox service, enabling you to load and invoke tools from your own applications.

Installation

pip install toolbox-core

Note

elasticsearch-esql

Mon, 01 Jan 0001 00:00:00 +0000

About

Execute ES|QL queries.

This tool allows you to execute ES|QL queries against your Elasticsearch cluster. You can use this to perform complex searches and aggregations.

See the official documentation for more information.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Elasticsearch

Parameters

name	type	required	description
query	string	false	The ES\|QL query to run. Can also be passed by parameters.
format	string	false	The format of the query. Default is json. Valid values are csv, json, tsv, txt, yaml, cbor, smile, or arrow.
timeout	integer	false	The timeout for the query in seconds. Default is 60 (1 minute).
parameters	parameters	false	List of parameters that will be used with the ES\|QL query. Only supports “string”, “integer”, “float”, “boolean”.

Example

kind: tool
name: query_my_index
type: elasticsearch-esql
source: elasticsearch-source
description: Use this tool to execute ES|QL queries.
query: |
 FROM my-index
 | KEEP *
 | LIMIT ?limit
parameters:
 - name: limit
 type: integer
 description: Limit the number of results.
 required: true

FAQ

Mon, 01 Jan 0001 00:00:00 +0000

How can I deploy or run Toolbox?

MCP Toolbox for Databases is open-source and can be run or deployed to a multitude of environments. For convenience, we release compiled binaries and docker images (but you can always compile yourself as well!).

For detailed instructions, check out these resources:

Do I need a Google Cloud account/project to get started with Toolbox?

Nope! While some of the sources Toolbox connects to may require GCP credentials, Toolbox doesn’t require them and can connect to a bunch of different resources that don’t.

Firestore using MCP

Mon, 01 Jan 0001 00:00:00 +0000

Redirecting to Firestore using MCP

Connecting to Firestore using MCP... If you are not automatically redirected, please click here to proceed.

Generic OIDC Auth

Mon, 01 Jan 0001 00:00:00 +0000

Getting Started

The Generic Auth Service allows you to integrate with any OpenID Connect (OIDC) compliant identity provider (IDP). It discovers the JWKS (JSON Web Key Set) URL either through the provider’s /.well-known/openid-configuration endpoint or directly via the provided authorizationServer.

To configure this auth service, you need to provide the audience (typically your client ID or the intended audience for the token), the authorizationServer of your identity provider, and optionally a list of scopesRequired that must be present in the token’s claims.

Looker using MCP

Mon, 01 Jan 0001 00:00:00 +0000

Model Context Protocol (MCP) is an open protocol for connecting Large Language Models (LLMs) to data sources like Postgres. This guide covers how to use MCP Toolbox for Databases to expose your developer assistant tools to a Looker instance:

Set up Looker

Get a Looker Client ID and Client Secret. Follow the directions here.
Have the base URL of your Looker instance available. It is likely something like https://looker.example.com. In some cases the API is listening at a different port, and you will need to use https://looker.example.com:19999 instead.

MySQL using MCP

Mon, 01 Jan 0001 00:00:00 +0000

Model Context Protocol (MCP) is an open protocol for connecting Large Language Models (LLMs) to data sources like MySQL. This guide covers how to use MCP Toolbox for Databases to expose your developer assistant tools to a MySQL instance:

Set up the database

Create or select a MySQL instance.

Install MCP Toolbox

Download the latest version of Toolbox as a binary. Select the correct binary corresponding to your OS and CPU architecture. You are required to use Toolbox version V0.10.0+:

Neo4j using MCP

Mon, 01 Jan 0001 00:00:00 +0000

Model Context Protocol (MCP) is an open protocol for connecting Large Language Models (LLMs) to data sources like Neo4j. This guide covers how to use MCP Toolbox for Databases to expose your developer assistant tools to a Neo4j instance:

Set up the database

Create or select a Neo4j instance.

Install MCP Toolbox

Download the latest version of Toolbox as a binary. Select the correct binary corresponding to your OS and CPU architecture. You are required to use Toolbox version v0.15.0+:

Oracle using MCP

Mon, 01 Jan 0001 00:00:00 +0000

Model Context Protocol (MCP) is an open protocol for connecting Large Language Models (LLMs) to data sources like Oracle. This guide covers how to use MCP Toolbox for Databases to expose your developer assistant tools to an Oracle instance:

Set up the database

Create or select an Oracle instance.
Create or reuse a database user and have the username and password ready.

PostgreSQL using MCP

Mon, 01 Jan 0001 00:00:00 +0000

Tip

Python Quickstart (Local)

Mon, 01 Jan 0001 00:00:00 +0000

Before you begin

This guide assumes you have already done the following:

Installed Python (3.10 or higher) (including pip and your preferred virtual environment tool for managing dependencies e.g. venv).
Installed PostgreSQL 16+ and the psql client.

Cloud Setup (Optional)

If you plan to use Google Cloud’s Vertex AI with your agent (e.g., using vertexai=True or a Google GenAI model), follow these one-time setup steps for local development:

Install the Google Cloud CLI

Quickstart (MCP with Looker and Gemini-CLI)

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Model Context Protocol is an open protocol that standardizes how applications provide context to LLMs. Check out this page on how to connect to Toolbox via MCP.

Step 1: Get a Looker Client ID and Client Secret

The Looker Client ID and Client Secret can be obtained from the Users page of your Looker instance. Refer to the documentation here. You may need to ask an administrator to get the Client ID and Client Secret for you.

serverless-spark-cancel-batch

Mon, 01 Jan 0001 00:00:00 +0000

About

serverless-spark-cancel-batch tool cancels a running Spark batch operation in a Google Cloud Serverless for Apache Spark source. The cancellation request is asynchronous, so the batch state will not change immediately after the tool returns; it can take a minute or so for the cancellation to be reflected.

serverless-spark-cancel-batch accepts the following parameters:

operation (required): The name of the operation to cancel. For example, for projects/my-project/locations/us-central1/operations/my-operation, you would pass my-operation.

The tool inherits the project and location from the source configuration.

serverless-spark-create-pyspark-batch

Mon, 01 Jan 0001 00:00:00 +0000

About

A serverless-spark-create-pyspark-batch tool submits a Spark batch to a Google Cloud Serverless for Apache Spark source. The workload executes asynchronously and takes around a minute to begin executing; status can be polled using the get batch tool.

serverless-spark-create-pyspark-batch accepts the following parameters:

mainFile: The path to the main Python file, as a gs://… URI.
args Optional. A list of arguments passed to the main file.
version Optional. The Serverless runtime version to execute with.

Compatible Sources

This tool can be used with the following database sources:

serverless-spark-create-spark-batch

Mon, 01 Jan 0001 00:00:00 +0000

About

A serverless-spark-create-spark-batch tool submits a Java Spark batch to a Google Cloud Serverless for Apache Spark source. The workload executes asynchronously and takes around a minute to begin executing; status can be polled using the get batch tool.

serverless-spark-create-spark-batch accepts the following parameters:

mainJarFile: Optional. The gs:// URI of the jar file that contains the main class. Exactly one of mainJarFile or mainClass must be specified.
mainClass: Optional. The name of the driver’s main class. Exactly one of mainJarFile or mainClass must be specified.
jarFiles: Optional. A list of gs:// URIs of jar files to add to the CLASSPATHs of the Spark driver and tasks.
args Optional. A list of arguments passed to the driver.
version Optional. The Serverless runtime version to execute with.

Compatible Sources

This tool can be used with the following database sources:

Spanner using MCP

Mon, 01 Jan 0001 00:00:00 +0000

Redirecting to Spanner using MCP

Connecting to Spanner using MCP... If you are not automatically redirected, please click here to proceed.

SQL Server using MCP

Mon, 01 Jan 0001 00:00:00 +0000

Model Context Protocol (MCP) is an open protocol for connecting Large Language Models (LLMs) to data sources like SQL Server. This guide covers how to use MCP Toolbox for Databases to expose your developer assistant tools to a SQL Server instance:

Set up the database

Create or select a SQL Server instance.

Install MCP Toolbox

Download the latest version of Toolbox as a binary. Select the correct binary corresponding to your OS and CPU architecture. You are required to use Toolbox version V0.10.0+:

SQLite using MCP

Mon, 01 Jan 0001 00:00:00 +0000

Model Context Protocol (MCP) is an open protocol for connecting Large Language Models (LLMs) to data sources like SQLite. This guide covers how to use MCP Toolbox for Databases to expose your developer assistant tools to a SQLite instance:

Set up the database

Create or select a SQLite database file.

Install MCP Toolbox

Download the latest version of Toolbox as a binary. Select the correct binary corresponding to your OS and CPU architecture. You are required to use Toolbox version V0.10.0+:

Telemetry

Mon, 01 Jan 0001 00:00:00 +0000

About

Telemetry data such as logs, metrics, and traces will help developers understand the internal state of the system. This page walks though different types of telemetry and observability available in Toolbox.

Toolbox exports telemetry data of logs via standard out/err, and traces/metrics through OpenTelemetry. Additional flags can be passed to Toolbox to enable different logging behavior, or to export metrics through a specific exporter.

Logging

The following flags can be used to customize Toolbox logging:

clickhouse-list-databases

Mon, 01 Jan 0001 00:00:00 +0000

About

A clickhouse-list-databases tool lists all available databases in a ClickHouse instance.

This tool executes the SHOW DATABASES command and returns a list of all databases accessible to the configured user, making it useful for database discovery and exploration tasks.

Compatible Sources

This tool can be used with the following database sources:

Source Name
ClickHouse

Example

kind: tool
name: list_clickhouse_databases
type: clickhouse-list-databases
source: my-clickhouse-instance
description: List all available databases in the ClickHouse instance

Output Format

The tool returns an array of objects, where each object contains:

Cloud SQL for PostgreSQL Admin using MCP

Mon, 01 Jan 0001 00:00:00 +0000

This guide covers how to use MCP Toolbox for Databases to expose your developer assistant tools to create and manage Cloud SQL for PostgreSQL instance, database and users:

Before you begin

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Make sure that billing is enabled for your Google Cloud project.

JS Quickstart (Local)

Mon, 01 Jan 0001 00:00:00 +0000

Before you begin

This guide assumes you have already done the following:

Installed Node.js (v18 or higher).
Installed PostgreSQL 16+ and the psql client.

Cloud Setup (Optional)

If you plan to use Google Cloud’s Vertex AI with your agent (e.g., using vertexai=True or a Google GenAI model), follow these one-time setup steps for local development:

Install the Google Cloud CLI
Set up Application Default Credentials (ADC)
Set your project and enable Vertex AI

LangChain/LangGraph

Mon, 01 Jan 0001 00:00:00 +0000

Overview

The toolbox-langchain package provides a Python interface to the MCP Toolbox service, enabling you to load and invoke tools from your own applications.

Installation

pip install toolbox-langchain

Quickstart

Here’s a minimal example to get you started using LangGraph:

from toolbox_langchain import ToolboxClient
from langchain_google_vertexai import ChatVertexAI
from langgraph.prebuilt import create_react_agent

async with ToolboxClient("http://127.0.0.1:5000") as toolbox:
 tools = toolbox.load_toolset()

 model = ChatVertexAI(model="gemini-3-flash-preview")
 agent = create_react_agent(model, tools)

 prompt = "How's the weather today?"

 for s in agent.stream({"messages": [("user", prompt)]}, stream_mode="values"):
 message = s["messages"][-1]
 if isinstance(message, tuple):
 print(message)
 else:
 message.pretty_print()

Tip

spanner-list-graphs

Mon, 01 Jan 0001 00:00:00 +0000

About

A spanner-list-graphs tool retrieves comprehensive schema information about graphs in a Cloud Spanner database. It returns detailed metadata including node tables, edge tables, labels and property declarations.

Features

Comprehensive Schema Information: Returns node tables, edge tables, labels and property declarations
Flexible Filtering: Can list all graphs or filter by specific graph names
Output Format Options: Choose between simple (graph names only) or detailed (full schema information) output

Use Cases

Database Documentation: Generate comprehensive documentation of your database schema
Schema Validation: Verify that expected graphs, node and edge exist
Migration Planning: Understand the current schema before making changes
Development Tools: Build tools that need to understand database structure
Audit and Compliance: Track schema changes and ensure compliance with data governance policies

This tool is read-only and executes pre-defined SQL queries against the INFORMATION_SCHEMA tables to gather metadata.

Warning

spanner-list-tables

Mon, 01 Jan 0001 00:00:00 +0000

About

A spanner-list-tables tool retrieves comprehensive schema information about tables in a Cloud Spanner database. It automatically adapts to the database dialect (GoogleSQL or PostgreSQL) and returns detailed metadata including columns, constraints, and indexes.

This tool is read-only and executes pre-defined SQL queries against the INFORMATION_SCHEMA tables to gather metadata. The tool automatically detects the database dialect from the source configuration and uses the appropriate SQL syntax.

Features

Automatic Dialect Detection: Adapts queries based on whether the database uses GoogleSQL or PostgreSQL dialect
Comprehensive Schema Information: Returns columns, data types, constraints, indexes, and table relationships
Flexible Filtering: Can list all tables or filter by specific table names
Output Format Options: Choose between simple (table names only) or detailed (full schema information) output

Use Cases

Database Documentation: Generate comprehensive documentation of your database schema
Schema Validation: Verify that expected tables and columns exist
Migration Planning: Understand the current schema before making changes
Development Tools: Build tools that need to understand database structure
Audit and Compliance: Track schema changes and ensure compliance with data governance policies

Compatible Sources

This tool can be used with the following database sources:

clickhouse-list-tables

Mon, 01 Jan 0001 00:00:00 +0000

About

A clickhouse-list-tables tool lists all available tables in a specified ClickHouse database.

This tool executes the SHOW TABLES FROM <database> command and returns a list of all tables in the specified database that are accessible to the configured user, making it useful for schema exploration and table discovery tasks.

Compatible Sources

This tool can be used with the following database sources:

Source Name
ClickHouse

Parameters

parameter	type	required	description
database	string	true	The database to list tables from.

Example

kind: tool
name: list_clickhouse_tables
type: clickhouse-list-tables
source: my-clickhouse-instance
description: List all tables in a specific ClickHouse database

Output Format

The tool returns an array of objects, where each object contains:

Cloud SQL for MySQL Admin using MCP

Mon, 01 Jan 0001 00:00:00 +0000

This guide covers how to use MCP Toolbox for Databases to expose your developer assistant tools to create and manage Cloud SQL for MySQL instance, database and users:

Before you begin

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Make sure that billing is enabled for your Google Cloud project.

Deploy ADK Agent and MCP Toolbox

Mon, 01 Jan 0001 00:00:00 +0000

Before you begin

This guide assumes you have already done the following:

Completed the Python Quickstart (Local) and have a working ADK agent running locally.
Installed the Google Cloud CLI.
A Google Cloud project with billing enabled.

Step 1: Deploy MCP Toolbox to Cloud Run

Before deploying your agent, your MCP Toolbox server needs to be accessible from the cloud. We will deploy MCP Toolbox to Cloud Run.

Follow the Deploy to Cloud Run guide to deploy your MCP Toolbox instance.

Go Quickstart (Local)

Mon, 01 Jan 0001 00:00:00 +0000

Before you begin

This guide assumes you have already done the following:

Installed Go (v1.24.2 or higher).
Installed PostgreSQL 16+ and the psql client.

Cloud Setup (Optional)

If you plan to use Google Cloud’s Vertex AI with your agent (e.g., using vertexai=True or a Google GenAI model), follow these one-time setup steps for local development:

Install the Google Cloud CLI
Set up Application Default Credentials (ADC)
Set your project and enable Vertex AI

LlamaIndex

Mon, 01 Jan 0001 00:00:00 +0000

Overview

The toolbox-llamaindex package provides a Python interface to the MCP Toolbox service, enabling you to load and invoke tools from your own applications.

Installation

pip install toolbox-llamaindex

Quickstart

Here’s a minimal example to get you started using LlamaIndex:

import asyncio

from llama_index.llms.google_genai import GoogleGenAI
from llama_index.core.agent.workflow import AgentWorkflow

from toolbox_llamaindex import ToolboxClient

async def run_agent():
 async with ToolboxClient("http://127.0.0.1:5000") as toolbox:
 tools = toolbox.load_toolset()

 vertex_model = GoogleGenAI(
 model="gemini-3-flash-preview",
 vertexai_config={"project": "project-id", "location": "us-central1"},
 )
 agent = AgentWorkflow.from_tools_or_functions(
 tools,
 llm=vertex_model,
 system_prompt="You are a helpful assistant.",
 )
 response = await agent.run(user_msg="Get some response from the agent.")
 print(response)

asyncio.run(run_agent())

Tip

Cloud SQL for SQL Server Admin using MCP

Mon, 01 Jan 0001 00:00:00 +0000

This guide covers how to use MCP Toolbox for Databases to expose your developer assistant tools to create and manage Cloud SQL for SQL Server instance, database and users:

Before you begin

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Make sure that billing is enabled for your Google Cloud project.

Export Telemetry

Mon, 01 Jan 0001 00:00:00 +0000

About

The OpenTelemetry Collector offers a vendor-agnostic implementation of how to receive, process and export telemetry data. It removes the need to run, operate, and maintain multiple agents/collectors.

Configure the Collector

To configure the collector, you will have to provide a configuration file. The configuration file consists of four classes of pipeline component that access telemetry data.

Receivers
Processors
Exporters
Connectors

Example of setting up the classes of pipeline components (in this example, we don’t use connectors):

Prompts using Gemini CLI

Mon, 01 Jan 0001 00:00:00 +0000

Before you begin

This guide assumes you have already done the following:

Installed PostgreSQL 16+ and the psql client.

Step 1: Set up your database

In this section, we will create a database, insert some data that needs to be accessed by our agent, and create a database user for Toolbox to connect with.

Connect to postgres using the psql command:
```
psql -h 127.0.0.1 -U postgres
```
Here, postgres denotes the default postgres superuser.

Quickstart (MCP with AlloyDB)

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Model Context Protocol is an open protocol that standardizes how applications provide context to LLMs. Check out this page on how to connect to Toolbox via MCP.

Before you begin

This guide assumes you have already done the following:

Create a AlloyDB cluster and instance with a database and user.
Connect to the instance using AlloyDB Studio, psql command-line tool, or any other PostgreSQL client.
Enable the pgvector and google_ml_integration extensions. These are required for Semantic Search and Natural Language to SQL tools. Run the following SQL commands:

Snowflake

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Model Context Protocol is an open protocol that standardizes how applications provide context to LLMs. Check out this page on how to connect to Toolbox via MCP.

Before you begin

This guide assumes you have already done the following:

Create a Snowflake account.
Connect to the instance using SnowSQL, or any other Snowflake client.

Step 1: Set up your environment

Copy the environment template and update it with your Snowflake credentials:

Style Guide

Mon, 01 Jan 0001 00:00:00 +0000

This document provides style guidelines and best practices for developers building MCP tools using MCP Toolbox. Following these standards ensures that agents can reason effectively, security is maintained, and user intent is met with high precision.

Combatting “Context Rot” and Tool Limits

Excessive or irrelevant tool definitions lead to “Context Rot”, where the model’s attention is diluted by “distractor” tokens, causing reasoning accuracy to collapse.

Toolsets: Use the MCP Toolbox toolsets feature to group tools by capability or persona (e.g., cloud-sql-admin vs. cloud-sql-data). This ensures the agent only sees tools relevant to its immediate intent.
Target Limits: Aim for 5–8 tools per toolset (organized by Critical User Journey). While the platform supports more, performance and accuracy are highest when the agent is exposed to a cognitively manageable list of actions. The current rule of thumb is to try to keep it to 40 tools per server as an upper limit, though even this amount may cause performance issues. Performance degrades as more tools are added, so teams should heavily weigh adding new tools against the negative impact on tool accuracy until other mechanisms are in place to deal with this.

Naming Conventions

Tool Names

Use snake_case with the pattern <action>_<resource>. Avoid product-specific prefixes, as agents can disambiguate tools by the MCP server name.

Toolbox UI

Mon, 01 Jan 0001 00:00:00 +0000

Toolbox UI is a built-in web interface that allows users to visually inspect and test out configured resources such as tools and toolsets.

Launching Toolbox UI

To launch Toolbox’s interactive UI, use the --ui flag.

./toolbox --ui

Toolbox UI will be served from the same host and port as the Toolbox Server, with the /ui suffix. Once Toolbox is launched, the following INFO log with Toolbox UI’s url will be shown:

alloydb-wait-for-operation

Mon, 01 Jan 0001 00:00:00 +0000

About

The alloydb-wait-for-operation tool is a utility tool that waits for a long-running AlloyDB operation to complete. It does this by polling the AlloyDB Admin API operation status endpoint until the operation is finished, using exponential backoff.

Parameter	Type	Description	Required
`project`	string	The GCP project ID.	Yes
`location`	string	The location of the operation (e.g., ‘us-central1’).	Yes
`operation`	string	The ID of the operation to wait for.	Yes

Info

cloud-sql-clone-instance

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-clone-instance tool clones a Cloud SQL instance using the Cloud SQL Admin API.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Example

Basic clone (current state)

kind: tool
name: clone-instance-basic
type: cloud-sql-clone-instance
source: cloud-sql-admin-source
description: "Creates an exact copy of a Cloud SQL instance. Supports configuring instance zones and high-availability setup through zone preferences."

Point-in-time recovery (PITR) clone

kind: tool
name: clone-instance-pitr
type: cloud-sql-clone-instance
source: cloud-sql-admin-source
description: "Creates an exact copy of a Cloud SQL instance at a specific point in time (PITR). Supports configuring instance zones and high-availability setup through zone preferences"

Reference

Tool Configuration

field	type	required	description
type	string	true	Must be “cloud-sql-clone-instance”.
source	string	true	The name of the `cloud-sql-admin` source to use.
description	string	false	A description of the tool.

Tool Inputs

parameter	type	required	description
project	string	true	The project ID.
sourceInstanceName	string	true	The name of the source instance to clone.
destinationInstanceName	string	true	The name of the new (cloned) instance.
pointInTime	string	false	(Optional) The point in time for a PITR (Point-In-Time Recovery) clone.
preferredZone	string	false	(Optional) The preferred zone for the cloned instance. If not specified, defaults to the source instance’s zone.
preferredSecondaryZone	string	false	(Optional) The preferred secondary zone for the cloned instance (for HA).

Advanced Usage

The tool supports both basic clone and point-in-time recovery (PITR) clone operations.
For PITR, specify the pointInTime parameter in RFC3339 format (e.g., 2024-01-01T00:00:00Z).
The source must be a valid Cloud SQL Admin API source.
You can optionally specify the zone parameter to set the zone for the cloned instance. If omitted, the zone of the source instance will be used.
You can optionally specify the preferredZone and preferredSecondaryZone (only in REGIONAL instances) to set the preferred zones for the cloned instance. These are useful for high availability (HA) configurations. If omitted, defaults will be used based on the source instance.

Additional Resources

cloud-sql-create-backup

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-create-backup tool creates an on-demand backup on a Cloud SQL instance using the Cloud SQL Admin API.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Parameters

parameter	type	required	description
project	string	true	The project ID.
instance	string	true	The name of the instance to take a backup on. Does not include the project ID.
location	string	false	(Optional) Location of the backup run.
backup_description	string	false	(Optional) The description of this backup run.

Example

Basic backup creation (current state)

cloud-sql-create-database

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-create-database tool creates a new database in a specified Cloud SQL instance.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Parameters

parameter	type	required	description
project	string	true	The project ID.
instance	string	true	The ID of the instance where the database will be created.
name	string	true	The name for the new database. Must be unique within the instance.

Example

kind: tool
name: create-cloud-sql-database
type: cloud-sql-create-database
source: my-cloud-sql-admin-source
description: "Creates a new database in a Cloud SQL instance."

Reference

field	type	required	description
type	string	true	Must be “cloud-sql-create-database”.
source	string	true	The name of the `cloud-sql-admin` source to use.
description	string	false	A description of the tool.

cloud-sql-create-users

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-create-users tool creates a new user in a specified Cloud SQL instance. It can create both built-in and IAM users.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Example

kind: tool
name: create-cloud-sql-user
type: cloud-sql-create-users
source: my-cloud-sql-admin-source
description: "Creates a new user in a Cloud SQL instance. Both built-in and IAM users are supported. IAM users require an email account as the user name. IAM is the more secure and recommended way to manage users. The agent should always ask the user what type of user they want to create. For more information, see https://cloud.google.com/sql/docs/postgres/add-manage-iam-users"

Reference

field	type	required	description
type	string	true	Must be “cloud-sql-create-users”.
description	string	false	A description of the tool.
source	string	true	The name of the `cloud-sql-admin` source to use.

cloud-sql-get-instance

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-get-instance tool retrieves a Cloud SQL instance resource using the Cloud SQL Admin API.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Example

kind: tool
name: get-sql-instance
type: cloud-sql-get-instance
source: my-cloud-sql-admin-source
description: "Gets a particular cloud sql instance."

Reference

field	type	required	description
type	string	true	Must be “cloud-sql-get-instance”.
source	string	true	The name of the `cloud-sql-admin` source to use.
description	string	false	A description of the tool.

cloud-sql-mssql-create-instance

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-mssql-create-instance tool creates a Cloud SQL for SQL Server instance using the Cloud SQL Admin API.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Example

kind: tool
name: create-sql-instance
type: cloud-sql-mssql-create-instance
source: cloud-sql-admin-source
description: "Creates a SQL Server instance using `Production` and `Development` presets. For the `Development` template, it chooses a 2 vCPU, 8 GiB RAM (`db-custom-2-8192`) configuration with Non-HA/zonal availability. For the `Production` template, it chooses a 4 vCPU, 26 GiB RAM (`db-custom-4-26624`) configuration with HA/regional availability. The Enterprise edition is used in both cases. The default database version is `SQLSERVER_2022_STANDARD`. The agent should ask the user if they want to use a different version."

Reference

Tool Configuration

field	type	required	description
type	string	true	Must be “cloud-sql-mssql-create-instance”.
source	string	true	The name of the `cloud-sql-admin` source to use.
description	string	false	A description of the tool.

Tool Inputs

parameter	type	required	description
project	string	true	The project ID.
name	string	true	The name of the instance.
databaseVersion	string	false	The database version for SQL Server. If not specified, defaults to the latest available version (e.g., SQLSERVER_2022_STANDARD).
rootPassword	string	true	The root password for the instance.
editionPreset	string	false	The edition of the instance. Can be `Production` or `Development`. This determines the default machine type and availability. Defaults to `Development`.

cloud-sql-postgres-create-instance

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-postgres-create-instance tool creates a Cloud SQL for PostgreSQL instance using the Cloud SQL Admin API.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Example

kind: tool
name: create-sql-instance
type: cloud-sql-postgres-create-instance
source: cloud-sql-admin-source
description: "Creates a Postgres instance using `Production` and `Development` presets. For the `Development` template, it chooses a 2 vCPU, 16 GiB RAM, 100 GiB SSD configuration with Non-HA/zonal availability. For the `Production` template, it chooses an 8 vCPU, 64 GiB RAM, 250 GiB SSD configuration with HA/regional availability. The Enterprise Plus edition is used in both cases. The default database version is `POSTGRES_17`. The agent should ask the user if they want to use a different version."

Reference

Tool Configuration

field	type	required	description
type	string	true	Must be “cloud-sql-postgres-create-instance”.
source	string	true	The name of the `cloud-sql-admin` source to use.
description	string	false	A description of the tool.

Tool Inputs

parameter	type	required	description
project	string	true	The project ID.
name	string	true	The name of the instance.
databaseVersion	string	false	The database version for Postgres. If not specified, defaults to the latest available version (e.g., POSTGRES_17).
rootPassword	string	true	The root password for the instance.
editionPreset	string	false	The edition of the instance. Can be `Production` or `Development`. This determines the default machine type and availability. Defaults to `Development`.

cloud-sql-restore-backup

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-restore-backup tool restores a backup on a Cloud SQL instance using the Cloud SQL Admin API.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Parameters

parameter	type	required	description
target_project	string	true	The project ID of the instance to restore the backup onto.
target_instance	string	true	The instance to restore the backup onto. Does not include the project ID.
backup_id	string	true	The identifier of the backup being restored.
source_project	string	false	(Optional) The project ID of the instance that the backup belongs to.
source_instance	string	false	(Optional) Cloud SQL instance ID of the instance that the backup belongs to.

Example

Basic backup restore

cloud-sql-wait-for-operation

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-sql-wait-for-operation tool is a utility tool that waits for a long-running Cloud SQL operation to complete. It does this by polling the Cloud SQL Admin API operation status endpoint until the operation is finished, using exponential backoff.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Example

kind: tool
name: cloudsql-operations-get
type: cloud-sql-wait-for-operation
source: my-cloud-sql-source
description: "This will poll on operations API until the operation is done. For checking operation status we need projectId and operationId. Once instance is created give follow up steps on how to use the variables to bring data plane MCP server up in local and remote setup."
delay: 1s
maxDelay: 4m
multiplier: 2
maxRetries: 10

Reference

field	type	required	description
type	string	true	Must be “cloud-sql-wait-for-operation”.
source	string	true	The name of a `cloud-sql-admin` source to use for authentication.
description	string	false	A description of the tool.
delay	duration	false	The initial delay between polling requests (e.g., `3s`). Defaults to 3 seconds.
maxDelay	duration	false	The maximum delay between polling requests (e.g., `4m`). Defaults to 4 minutes.
multiplier	float	false	The multiplier for the polling delay. The delay is multiplied by this value after each request. Defaults to 2.0.
maxRetries	int	false	The maximum number of polling attempts before giving up. Defaults to 10.

Invoke Tools via CLI

Mon, 01 Jan 0001 00:00:00 +0000

The invoke command allows you to invoke tools defined in your configuration directly from the CLI. This is useful for:

Ephemeral Invocation: Executing a tool without spinning up a full MCP server/client.
Debugging: Isolating tool execution logic and testing with various parameter combinations.

Tip

Versioning Policy

Mon, 01 Jan 0001 00:00:00 +0000

MCP Toolbox for Databases follows Semantic Versioning.

Definition of the Public API

For the purposes of this policy, the “Public API” includes:

Server
- CLI: The execution engine and lifecycle manager for tool hosting.
- Configuration Manifests: The structural specification of tools.yaml.
- Pre-built Configs: Curated sets of tools (and other MCP primitives) including the CLI flag, source configuration, toolsets names, and tools.
- MCP versions: Supporting MCP revisions and transport protocols.
Client SDKs: Both the foundational “Base SDKs” and the orchestration-specific “Integrated SDKs”.

What Constitutes a Breaking Change (Major Version Bump)

A major version bump (e.g., v1.x.x to v2.0.0) is required for the following modifications:

postgres-upgrade-precheck

Mon, 01 Jan 0001 00:00:00 +0000

About

The postgres-upgrade-precheck tool initiates a pre-check on a Cloud SQL for PostgreSQL instance to assess its readiness for a major version upgrade using the Cloud SQL Admin API. It helps identify potential incompatibilities or issues before starting the actual upgrade process.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL Admin

Example

kind: tool
name: postgres-upgrade-precheck
type: postgres-upgrade-precheck
source: cloud-sql-admin-source
description: "Checks if a Cloud SQL PostgreSQL instance is ready for a major version upgrade to the specified target version."

Reference

field	type	required	description
type	string	true	Must be “postgres-upgrade-precheck”.
source	string	true	The name of the `cloud-sql-admin` source to use.
description	string	false	A description of the tool.

parameter	type	required	description
project	string	true	The project ID containing the instance.
instance	string	true	The name of the Cloud SQL instance to check.
targetDatabaseVersion	string	false	The target PostgreSQL major version for the upgrade (e.g., `POSTGRES_18`). If not specified, defaults to the PostgreSQL 18.

Getting started with alloydb-ai-nl tool

Mon, 01 Jan 0001 00:00:00 +0000

Objective

In this notebook, we will be using the AlloyDB AI NL tool to generate and execute SQL queries on AlloyDB databases. We will start by setting up an AlloyDB database and then connecting to it using MCP Toolbox and ADK. This allows us to leverage AlloyDB NL to SQL capabilities in agentic applications.

For detailed information on the AlloyDB capability, please see AlloyDB AI Natural Language Overview.

Before you Begin

Complete the before you begin setup from Use AlloyDB AI natural language to generate SQL.

cloud-logging-admin-list-log-names

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-logging-admin-list-log-names tool lists the log names available in the Google Cloud project.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Logging Admin

Example

kind: tool
name: list_log_names
type: cloud-logging-admin-list-log-names
source: my-cloud-logging
description: Lists all log names in the project.

Reference

field	type	required	description
type	string	true	Must be “cloud-logging-admin-list-log-names”.
source	string	true	Name of the cloud-logging-admin source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

parameter	type	required	description
limit	integer	false	Maximum number of log entries to return (default: 200).

cloud-logging-admin-list-resource-types

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-logging-admin-list-resource-types tool lists the monitored resource types available in Google Cloud Logging.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Logging Admin

Example

kind: tool
name: list_resource_types
type: cloud-logging-admin-list-resource-types
source: my-cloud-logging
description: Lists monitored resource types.

Reference

field	type	required	description
type	string	true	Must be “cloud-logging-admin-list-resource-types”.
source	string	true	Name of the cloud-logging-admin source.
description	string	true	Description of the tool that is passed to the LLM.

cloud-logging-admin-query-logs

Mon, 01 Jan 0001 00:00:00 +0000

About

The cloud-logging-admin-query-logs tool allows you to query log entries from Google Cloud Logging using the advanced logs filter syntax.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud Logging Admin

Example

kind: tool
name: query_logs
type: cloud-logging-admin-query-logs
source: my-cloud-logging
description: Queries log entries from Cloud Logging.

Reference

field	type	required	description
type	string	true	Must be “cloud-logging-admin-query-logs”.
source	string	true	Name of the cloud-logging-admin source.
description	string	true	Description of the tool that is passed to the LLM.

Parameters

parameter	type	required	description
filter	string	false	Cloud Logging filter query. Common fields: resource.type, resource.labels., logName, severity, textPayload, jsonPayload., protoPayload., labels., httpRequest.*. Operators: =, !=, <, <=, >, >=, :, =~, AND, OR, NOT.
newestFirst	boolean	false	Set to true for newest logs first. Defaults to oldest first.
startTime	string	false	Start time in RFC3339 format (e.g., 2025-12-09T00:00:00Z). Defaults to 30 days ago.
endTime	string	false	End time in RFC3339 format (e.g., 2025-12-09T23:59:59Z). Defaults to now.
verbose	boolean	false	Include additional fields (insertId, trace, spanId, httpRequest, labels, operation, sourceLocation). Defaults to false.
limit	integer	false	Maximum number of log entries to return. Default: `200`.