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MCP Search Analytics Server

@dexter480

代码仓库

基本信息

分类

数据与分析

传输方式

stdio

作者

dexter480

关于 MCP Search Analytics Server

MCP server for GA and GSC data analysis

#mcp#search-analytics#data-analysis

MCP Search Analytics Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-search-analytics": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MCP Search Analytics Server 工具

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。

概览

What is MCP Search Analytics Server?

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.

How to use MCP Search Analytics Server?

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.

Key features of MCP Search Analytics Server

  • Unified access to GA4 and Search Console data
  • Real‑time analytics queries via MCP interface
  • Secure credential management through environment variables
  • Built‑in credential testing script

Use cases of MCP Search Analytics Server

  • Query website traffic and search performance data through an MCP‑compatible AI assistant
  • Combine Google Analytics and Search Console metrics in a single request
  • Automate analytics data retrieval in AI‑powered data analysis pipelines

常见问题

1

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.

2

How do I configure the server?

Copy `environment.example` to `.env` and set the `ANALYTICS_CREDENTIALS_PATH`, `GSC_SITE_URL`, and `GA4_PROPERTY_ID` variables with your actual values.

3

What security precautions are recommended?

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.

4

How can I test that my setup is working?

Run `python test_credentials.py` to verify your credentials before starting the server.

5

Where can I find the full list of Python dependencies?

The `requirements.txt` file in the repository lists all required Python packages.

评论

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