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Showing content from https://github.com/LucasHild/mcp-server-bigquery below:

LucasHild/mcp-server-bigquery: A Model Context Protocol server that provides access to BigQuery

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

The server implements one tool:

execute-query: Executes a SQL query using BigQuery dialect
list-tables: Lists all tables in the BigQuery database
describe-table: Describes the schema of a specific table

The server can be configured either with command line arguments or environment variables.

Argument Environment Variable Required Description --project BIGQUERY_PROJECT Yes The GCP project ID. --location BIGQUERY_LOCATION Yes The GCP location (e.g. europe-west9). --dataset BIGQUERY_DATASETS No Only take specific BigQuery datasets into consideration. Several datasets can be specified by repeating the argument (e.g. --dataset my_dataset_1 --dataset my_dataset_2) or by joining them with a comma in the environment variable (e.g. BIGQUERY_DATASETS=my_dataset_1,my_dataset_2). If not provided, all datasets in the project will be considered. --key-file BIGQUERY_KEY_FILE No Path to a service account key file for BigQuery. If not provided, the server will use the default credentials.

To install BigQuery Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install mcp-server-bigquery --client claude

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

Development/Unpublished Servers Configuration

"mcpServers": {
  "bigquery": {
    "command": "uv",
    "args": [
      "--directory",
      "{{PATH_TO_REPO}}",
      "run",
      "mcp-server-bigquery",
      "--project",
      "{{GCP_PROJECT_ID}}",
      "--location",
      "{{GCP_LOCATION}}"
    ]
  }
}

Published Servers Configuration

"mcpServers": {
  "bigquery": {
    "command": "uvx",
    "args": [
      "mcp-server-bigquery",
      "--project",
      "{{GCP_PROJECT_ID}}",
      "--location",
      "{{GCP_LOCATION}}"
    ]
  }
}

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

To prepare the package for distribution:

Increase the version number in pyproject.toml
Sync dependencies and update lockfile:

Build package distributions:

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

Publish to PyPI:

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

Token: --token or UV_PUBLISH_TOKEN
Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

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.

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