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BigQuery MCP server

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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:

  • 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

Configuration

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.

Quickstart

Install

Installing via Smithery

To install BigQuery Server for Claude Desktop automatically via Smithery:

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

Claude Desktop

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Development/Unpublished Servers Configuration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.

Development

Building and Publishing

To prepare the package for distribution:

  1. Increase the version number in pyproject.toml

  2. 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:

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

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.

Metadata

Release files for iflow-mcp_mcp-server-bigquery 0.3.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for iflow-mcp_mcp-server-bigquery 0.3.1
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Built distribution (wheel)

Table of built distributions (wheels) for iflow-mcp_mcp-server-bigquery 0.3.1
File Interpreter ABI Platform
iflow_mcp_mcp_server_bigquery-0.3.1-py3-none-any.whl Python 3 none any Details

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