What are the prerequisites?
Python 3.10 or higher, a Google Cloud project with the Search Console API enabled, and a service account with access to Search Console.
@guchey
基本情報
概要はまだありません
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-google-search-console": {
"command": "uv",
"args": [
"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。
The Google Search Console MCP Server is a tool that enables AI assistants (via the Model Context Protocol) to retrieve and analyze search performance data from Google Search Console. It is intended for developers and SEO professionals who want to integrate search analytics into AI workflows, providing programmatic access to metrics like clicks, impressions, and rankings.
Install with pip install mcp-server-google-search-console and set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path of your service account JSON key. Start the server with mcp-server-gsc (or uvx run mcp-server-gsc). Configure Claude Desktop by adding a gsc entry to the mcpServers object, specifying the command and environment variable. Use the search_analytics tool with required parameters siteUrl, startDate, and endDate.
Python 3.10 or higher, a Google Cloud project with the Search Console API enabled, and a service account with access to Search Console.
Set the environment variable `GOOGLE_APPLICATION_CREDENTIALS` to the path of your downloaded JSON key from the Google Cloud Console.
`siteUrl` (site URL), `startDate`, and `endDate` (both in YYYY-MM-DD format). Optional parameters include `dimensions`, `type`, `aggregationType`, and `rowLimit`.
Yes, using `uvx run mcp-server-gsc` with optional Python version and environment variable flags.
Add a JSON entry to Claude’s MCP configuration with `command: "mcp-server-gsc"` and the `GOOGLE_APPLICATION_CREDENTIALS` environment variable. An alternative using `uvx` is also provided.
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