BigQuery MCP server

Name: BigQuery MCP server
Author: LucasHild

@LucasHild

リポジトリ

BigQuery MCP server について

A Model Context Protocol server that provides access to BigQuery

#bigquery #database-querying #llm-integration

基本情報

カテゴリ

データベース

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

LucasHild

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": {
    "mcp-server-bigquery": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli",
        "install",
        "mcp-server-bigquery",
        "--client",
        "claude"
      ]
    }
  }
}

ツール

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 provides access to BigQuery, enabling LLMs to inspect database schemas and execute queries. It is intended for developers using AI assistants to interact with BigQuery data.

How to use BigQuery MCP server?

Install via Smithery using npx -y @smithery/cli install mcp-server-bigquery --client claude or configure directly in client configs (Claude Desktop, Claude Code, Cursor). Required configuration: project ID (via --project argument or BIGQUERY_PROJECT env var) and location (via --location or BIGQUERY_LOCATION). Run with uvx mcp-server-bigquery.

Key features of BigQuery MCP server

Provides three tools: execute-query, list-tables, describe-table
Configurable via command line arguments or environment variables
Supports filtering by specific BigQuery datasets
Can use a service account key file or default credentials
Optional query timeout setting

Use cases of BigQuery MCP server

Enabling LLMs to discover BigQuery table schemas
Running SQL queries against BigQuery from an AI assistant
Interacting with BigQuery data without leaving the chat interface

FAQ from BigQuery MCP server

What tools does the BigQuery MCP server implement?

It implements three tools: execute-query (executes a SQL query using BigQuery dialect), list-tables (lists all tables in the database), and describe-table (describes the schema of a specific table).

What are the required configuration settings?

The GCP project ID and location are required. They can be provided via command line arguments (--project, --location) or environment variables (BIGQUERY_PROJECT, BIGQUERY_LOCATION).

Can I limit access to specific datasets?

Yes, use the --dataset argument (repeatable) or BIGQUERY_DATASETS environment variable with comma-separated dataset names. If not provided, all datasets in the project are considered.

How do I authenticate with BigQuery?

Either provide a path to a service account key file via --key-file or BIGQUERY_KEY_FILE, or omit it to use default credentials (e.g., from the environment or gcloud).

Is there a query timeout?

An optional --timeout argument (or BIGQUERY_TIMEOUT env var) sets the maximum time in seconds to wait for query completion. If not provided, queries wait indefinitely.