What are the prerequisites?
Python 3.8+, a Google Cloud Project with the Analytics Reporting API and Search Console API enabled, and a Google Service Account with appropriate permissions.
@dexter480
基本情報
MCP server for GA and GSC data analysis
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-search-analytics": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
MCP Search Analytics Server is a Model Context Protocol (MCP) server that provides unified access to Google Analytics 4 and Google Search Console data, enabling real-time analytics queries through the MCP interface. It is designed for developers and data analysts who need to integrate analytics data into AI‑assisted workflows.
Install Python dependencies (Python 3.8+ required), configure environment variables for your Google service account credentials, Search Console site URL, and GA4 property ID in a .env file, then run the server with python unified_analytics_server.py. Test your credentials first with python test_credentials.py.
Python 3.8+, a Google Cloud Project with the Analytics Reporting API and Search Console API enabled, and a Google Service Account with appropriate permissions.
Copy `environment.example` to `.env` and set the `ANALYTICS_CREDENTIALS_PATH`, `GSC_SITE_URL`, and `GA4_PROPERTY_ID` variables with your actual values.
Never commit credential files (`.json`, `.env`) to version control, store credentials securely, rotate service account keys regularly, and follow the principle of least privilege for API access.
Run `python test_credentials.py` to verify your credentials before starting the server.
The `requirements.txt` file in the repository lists all required Python packages.

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