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BigQuery MCP server

A Model Context Protocol server that provides access to BigQuery. This server enables LLMs to inspect database schemas and execute queries.

Components

Tools

The server implements one tool:

Configuration

The server can be configured with the following arguments:

Quickstart

Install

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

<details> <summary>Development/Unpublished Servers Configuration</summary> ``` "mcpServers": { "bigquery": { "command": "uv", "args": [ "--directory", "{{PATH_TO_REPO}}", "run", "mcp-server-bigquery", "--project", "{{GCP_PROJECT_ID}}", "--location", "{{GCP_LOCATION}}" ] } } ``` </details> <details> <summary>Published Servers Configuration</summary> ``` "mcpServers": { "bigquery": { "command": "uvx", "args": [ "mcp-server-bigquery", "--project", "{{GCP_PROJECT_ID}}", "--location", "{{GCP_LOCATION}}" ] } } ``` </details>

Replace {{PATH_TO_REPO}}, {{GCP_PROJECT_ID}}, and {{GCP_LOCATION}} with the appropriate values.

Development

Building and Publishing

To prepare the package for distribution:

  1. Sync dependencies and update lockfile:
uv sync
  1. Build package distributions:
uv build

This will create source and wheel distributions in the dist/ directory.

  1. Publish to PyPI:
uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory {{PATH_TO_REPO}} run mcp-server-bigquery

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.