Googlebigquery Automation

Google BigQuery Automation via Rube MCP

Run SQL queries, explore database schemas, and analyze datasets through the Metabase integration using Rube MCP (Composio).

Toolkit docs: composio.dev/toolkits/googlebigquery

Prerequisites

• Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
• Active connection via RUBE_MANAGE_CONNECTIONS with toolkit metabase
• A Metabase instance connected to your BigQuery data source
• Always call RUBE_SEARCH_TOOLS first to get current tool schemas

Setup

Get Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.

1. Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds
2. Call RUBE_MANAGE_CONNECTIONS with toolkit metabase
3. If connection is not ACTIVE, follow the returned auth link to complete setup
4. Confirm connection status shows ACTIVE before running any workflows

Note: BigQuery data is accessed through Metabase, a business intelligence tool that connects to BigQuery as a data source. The tools below execute queries and retrieve metadata through Metabase's API.

Core Workflows

1. Run a Native SQL Query

Use METABASE_POST_API_DATASET with type native to execute raw SQL queries against your BigQuery database.

Tool: METABASE_POST_API_DATASET
Parameters:
  - database (required): Metabase database ID (integer)
  - type (required): "native" for SQL queries
  - native (required): Object with "query" string
    - query: Raw SQL string (e.g., "SELECT * FROM users LIMIT 10")
    - template_tags: Parameterized query variables (optional)
  - constraints: { "max-results": 1000 } (optional)

2. Run a Structured MBQL Query

Use METABASE_POST_API_DATASET with type query for Metabase Query Language queries with built-in aggregation and filtering.

Tool: METABASE_POST_API_DATASET
Parameters:
  - database (required): Metabase database ID
  - type (required): "query" for MBQL
  - query (required): Object with:
    - source-table: Table ID (integer)
    - aggregation: e.g., [["count"]] or [["sum", ["field", 5, null]]]
    - breakout: Group-by fields
    - filter: Filter conditions
    - limit: Max rows
    - order-by: Sort fields

3. Get Query Metadata

Use METABASE_POST_API_DATASET_QUERY_METADATA to retrieve metadata about databases, tables, and fields available for querying.

Tool: METABASE_POST_API_DATASET_QUERY_METADATA
Parameters:
  - database (required): Metabase database ID
  - type (required): "query" or "native"
  - query (required): Query object (e.g., {"source-table": 1})

4. Convert Query to Native SQL

Use METABASE_POST_API_DATASET_NATIVE to convert an MBQL query into its native SQL representation.

Tool: METABASE_POST_API_DATASET_NATIVE
Parameters:
  - database (required): Metabase database ID
  - type (required): "native"
  - native (required): Object with "query" and optional "template_tags"
  - parameters: Query parameter values (optional)

5. List Available Databases

Use METABASE_GET_API_DATABASE to discover all database connections configured in Metabase.

Tool: METABASE_GET_API_DATABASE
Description: Retrieves a list of all Database instances configured in Metabase.
Note: Call RUBE_SEARCH_TOOLS to get the full schema for this tool.

6. Get Database Schema Metadata

Use METABASE_GET_API_DATABASE_ID_METADATA to retrieve complete table and field information for a specific database.

Tool: METABASE_GET_API_DATABASE_ID_METADATA
Description: Retrieves complete metadata for a specific database including
  all tables and fields.
Note: Call RUBE_SEARCH_TOOLS to get the full schema for this tool.

Common Patterns

• Discover then query: Use METABASE_GET_API_DATABASE to find database IDs, then METABASE_GET_API_DATABASE_ID_METADATA to explore tables and fields, then METABASE_POST_API_DATASET to run queries.
• SQL-first approach: Use METABASE_POST_API_DATASET with type: "native" and write standard SQL queries for maximum flexibility.
• Parameterized queries: Use template_tags in native queries for safe parameterization (e.g., SELECT * FROM users WHERE id = {{user_id}}).
• Schema exploration: Use METABASE_POST_API_DATASET_QUERY_METADATA to understand table structures before building complex queries.
• Get parameter values: Use METABASE_POST_API_DATASET_PARAMETER_VALUES to retrieve possible values for filter dropdowns.

Known Pitfalls

• The database parameter is a Metabase-internal integer ID, not the BigQuery project or dataset name. Use METABASE_GET_API_DATABASE to find valid database IDs first.
• source-table in MBQL queries is also a Metabase-internal integer, not the BigQuery table name. Discover table IDs via metadata tools.
• Native SQL queries use BigQuery SQL dialect (Standard SQL). Ensure your syntax is BigQuery-compatible.
• max-results in constraints defaults can limit returned rows. Set explicitly for large result sets.
• Responses from METABASE_POST_API_DATASET contain results nested under data -- parse carefully as the structure may be deeply nested.
• Metabase field IDs used in MBQL aggregation, breakout, and filter arrays must be integers obtained from metadata responses.

Quick Reference

Powered by Composio

Source: ComposioHQ/awesome-claude-skills → composio-skills/googlebigquery-automation/SKILL.md

Also appears in: composio-community/awesome-codex-skills/composio-skills/googlebigquery-automation/SKILL.md