Tools on MCP Toolbox for Databases

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 Source

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.

conversational-analytics-ask-data-agent

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

About

A conversational-analytics-ask-data-agent 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 a specific BigQuery Data Agent, 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.

conversational-analytics-get-data-agent-info

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

About

A conversational-analytics-get-data-agent-info tool allows you to retrieve details about a specific data agent.

It’s compatible with the following sources:

cloud-gemini-data-analytics

conversational-analytics-get-data-agent-info accepts the following parameters:

data_agent_id: The ID of the data agent to retrieve information for.

Example

kind: tool
name: get_agent_info
type: conversational-analytics-get-data-agent-info
source: my-conversational-analytics-source
location: global
description: |
 Use this tool to get details about a specific data agent.

Reference

field	type	required	description
type	string	true	Must be “conversational-analytics-get-data-agent-info”.
source	string	true	Name of the source.
description	string	true	Description of the tool that is passed to the LLM.
location	string	false	The Google Cloud location (default: “global”).

conversational-analytics-list-accessible-data-agents

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

About

A conversational-analytics-list-accessible-data-agents tool allows you to list data agents that are accessible.

The Conversational Analytics API returns accessible data agents one page at a time. By default this tool hides that: it follows every page itself and returns all accessible data agents in a single response. Set page_size or page_token to take over pagination and receive one page at a time instead.

It’s compatible with the following sources:

cloud-gemini-data-analytics

conversational-analytics-list-accessible-data-agents accepts the following parameters: