MCP Search Analytics Server

MCP Search Analytics Server

A Model Context Protocol (MCP) server for Google Analytics and Search Console data analysis.

🚀 Features

• Unified access to Google Analytics 4 and Google Search Console data
• Real-time analytics queries through MCP interface
• Secure credential management via environment variables

🔧 Setup

Prerequisites

• Python 3.8+
• Google Cloud Project with Analytics and Search Console APIs enabled
• Google Service Account with appropriate permissions

Installation

1. Clone this repository:

git clone https://github.com/vesivanov/mcp-search-analytics.git
cd mcp-search-analytics

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

Configuration

1. Create environment file:

   cp environment.example .env
   

2. Set up Google Service Account:

   • Create a service account in Google Cloud Console
   • Download the JSON credentials file
   • Enable Google Analytics Reporting API and Search Console API
   • Grant necessary permissions to your service account

3. Configure environment variables: Edit .env file with your actual values:

   ANALYTICS_CREDENTIALS_PATH=/path/to/your/credentials.json
   GSC_SITE_URL=https://your-website.com
   GA4_PROPERTY_ID=your-property-id
   

Usage

1. Test your credentials:

python test_credentials.py

2. Run the MCP server:

python unified_analytics_server.py

🔐 Security Notes

• Never commit credential files (.json, .env) to version control
• Store credentials securely and use environment variables
• Regularly rotate service account keys
• Follow principle of least privilege for API access

📋 Requirements

See requirements.txt for Python dependencies.

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.