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MCP Search Analytics Server

@dexter480

Repository

Basic information

Category

Data & Analytics

Transports

stdio

Author

dexter480

About MCP Search Analytics Server

MCP server for GA and GSC data analysis

#mcp#search-analytics#data-analysis

MCP Search Analytics Server config

Add this server to your MCP-compatible client using the configuration below.

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

MCP Search Analytics Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

Frequently asked questions

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.

Comments

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