BigQuery Analysis MCP Server

What is BigQuery Analysis MCP Server?

BigQuery Analysis MCP Server is a Model Context Protocol server for executing SQL queries against Google BigQuery. It validates queries (dry run), estimates processing size, and safely runs only SELECT queries under 1TB to prevent data modifications. Results are returned in JSON format. It is intended for users who need to query BigQuery through MCP-compatible clients like Claude Desktop.

How to use BigQuery Analysis MCP Server?

Install dependencies with npm install, build with npm run build, then configure the server in Claude Desktop’s claude_desktop_config.json (MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%/Claude/claude_desktop_config.json) providing the path to the built index.js. Authenticate with Google Cloud via gcloud CLI or a service account key. Use the provided tools dry_run_query and run_query_with_validation through the MCP client.

Key features of BigQuery Analysis MCP Server

• Query validation (dry run) with processing size estimation
• Safe query execution: only SELECT queries under 1TB
• Rejects DML statements (data modification queries)
• Returns results in structured JSON format
• Prevents accidental large data processing (>1TB)
• Developed with Node.js and requires Google Cloud authentication

Use cases of BigQuery Analysis MCP Server

• Validate a BigQuery query before execution to catch errors and estimate cost
• Run safe, read-only queries against BigQuery public datasets or custom tables
• Integrate BigQuery analysis into MCP-based AI assistants or automation tools
• Prevent accidental data modifications or runaway query costs in a team environment

FAQ from BigQuery Analysis MCP Server

What authentication does BigQuery Analysis MCP Server require?

It uses Google Cloud authentication via gcloud CLI (gcloud auth application-default login) or a service account key (set GOOGLE_APPLICATION_CREDENTIALS environment variable).

What types of queries are allowed?

Only SELECT queries under 1TB estimated processing size are allowed. DML statements (INSERT, UPDATE, DELETE, etc.) are automatically rejected.

How are query results returned?

Results are returned in JSON format after successful execution.

What are the runtime prerequisites?

Node.js v16 or higher and proper Google Cloud authentication are required.

How can I debug the server?

Use the MCP Inspector by running npm run inspector in the project directory, which provides a URL for browser-based debugging tools.