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BigQuery MCP server

@MCP-Mirror

BigQuery MCP server について

Mirror of

基本情報

カテゴリ

データベース

トランスポート

stdio

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MCP-Mirror

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "LucasHild_mcp-server-bigquery": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

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3

Executes a SQL query using BigQuery dialect

Lists all tables in the BigQuery database

Describes the schema of a specific table

概要

What is BigQuery MCP server?

A Model Context Protocol server that gives LLMs access to Google BigQuery. It lets AI assistants inspect database schemas and execute SQL queries directly against BigQuery datasets.

How to use BigQuery MCP server?

Install via uvx mcp-server-bigquery and configure it in your MCP client (e.g., Claude Desktop) by passing --project (required), --location (required), and optionally --dataset (repeatable). The server runs over stdio and exposes three tools.

Key features of BigQuery MCP server

  • Execute arbitrary SQL queries using BigQuery dialect
  • List all tables in the configured project/datasets
  • Describe the schema of a specific table
  • Filter which datasets are available to the LLM
  • Published on PyPI for easy installation

Use cases of BigQuery MCP server

  • Let an LLM assistant answer natural-language questions by querying BigQuery
  • Automate schema discovery and documentation generation
  • Build a natural-language interface for business analysts to explore data
  • Integrate BigQuery querying into AI-powered coding or analysis workflows

FAQ from BigQuery MCP server

What tools does BigQuery MCP server provide?

It provides three tools: execute-query, list-tables, and describe-table.

How do I restrict which datasets the server can access?

Use the --dataset argument (repeatable) to specify one or more datasets. If omitted, all tables in the project are considered.

What are the required configuration arguments?

You must provide --project (the GCP project ID) and --location (the GCP location, e.g. europe-west9).

Is BigQuery MCP server published on PyPI?

Yes. It can be run via uvx mcp-server-bigquery without a local checkout.

How can I debug the server?

Use the MCP Inspector. Run npx @modelcontextprotocol/inspector uv --directory <PATH> run mcp-server-bigquery to get a debugging URL.

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