mcp-groundx-rag-server

Jeevanpradhan571/mcp-groundx-rag-server

3.1

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The MCP-GroundX RAG Integration server is designed to facilitate AI-powered document search by integrating with the GroundX RAG platform, enabling seamless retrieval of information from document collections.

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MCP-GroundX RAG Integration: AI-Powered Document Search Server

A Model Context Protocol (MCP) server that integrates with GroundX RAG platform to enable AI assistants to search and retrieve information from document collections.

🚀 Features

  • RAG Integration: Seamless integration with GroundX's document search capabilities
  • MCP Protocol: Standard protocol for AI tool integration
  • Semantic Search: Advanced document retrieval using vector embeddings
  • Real-time Queries: Fast, responsive document search
  • Secure API Management: Environment-based configuration

🛠️ Technologies Used

  • Python 3 - Core programming language
  • FastMCP - MCP server framework
  • GroundX SDK - Document search and RAG platform
  • python-dotenv - Environment variable management

📋 Prerequisites

  • Python 3.7+
  • GroundX account and API key
  • Git

🔧 Installation

  1. Clone the repository

    git clone <your-repo-url>
cd MCP

  2. Install dependencies

    pip install mcp-server-fastmcp groundx python-dotenv

  3. Set up environment variables

    cp env.example .env

    Edit .env file and add your GroundX API key:

    GROUNDX_API_KEY=your_groundx_api_key_here

🚀 Usage

  1. Start the MCP server

    python3 server.py

  2. Connect with MCP clients The server provides a tool called search_doc_for_rag_context that accepts query strings and returns relevant document excerpts.

📁 Project Structure

MCP/
├── server.py          # Main MCP server implementation
├── .env               # Environment variables (not in repo)
├── env.example        # Example environment file
├── .gitignore         # Git ignore rules
├── requirements.txt   # Python dependencies
└── README.md          # This file

🔧 Configuration

Environment Variables

  • GROUNDX_API_KEY: Your GroundX API key (required)

GroundX Database

The server is configured to search GroundX database ID 19859. To use a different database:

  1. Update the id parameter in server.py: 
    response = client.search.content(
    id=YOUR_DATABASE_ID,  # Change this
    query=query,
    n=10,
)

🛠️ API Reference

MCP Tool: search_doc_for_rag_context

Parameters:

  • query (string): Search query for document retrieval

Returns:

  • string: Relevant document excerpts from GroundX database

Example:

# Query for aircraft specifications
result = search_doc_for_rag_context("MIG 29 aircraft dimensions")

🔒 Security

  • API keys are stored in environment variables (not in code)
  • .env file is excluded from version control
  • Use env.example as a template for configuration

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📄 License

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

🙏 Acknowledgments

📞 Support

For issues and questions: