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
基本信息
暂无概览
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server-google-search-console": {
"command": "uv",
"args": [
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
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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