MCP VectorStore Server

# Quick Installation Guide ## Prerequisites - Python 3.8+ - 4GB+ RAM - Internet connection ## Quick Start (Linux/macOS) 1. **Clone or download the files to your system** 2. **Run the automated setup:** ```bash chmod +x start_server.sh ./start_server.sh ``` This script will: - Create a virtual environment - Install all dependencies - Check for LLMSherpa server - Start the MCP server ## Manual Installation ### Step 1: Environment Setup ```bash python3 -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate ``` ### Step 2: Install Dependencies ```bash pip install --upgrade pip pip install -r requirements.txt ``` ### Step 3: Optional: Start LLMSherpa ```bash pip install llmsherpa llmsherpa --port 5001 ``` ### Step 4: Start Server ```bash python mcp_vectorstore_server.py ``` ## Configuration 1. **Edit `config.json`** to customize settings 2. **Create `.env`** file for environment variables (optional) 3. **Update document directory** in `config.json` ## Testing ```bash # Test basic functionality python -c "from mcp_vectorstore_server import *; print('Server ready!')" # Test vector store python -c "from vectorstore import PDFVectorStoreTool; tool = PDFVectorStoreTool(); print(f'Documents: {tool.vectorstore_get_num_items()}')" ``` ## Troubleshooting - **Import errors**: Run `pip install -r requirements.txt` - **CUDA errors**: Use CPU-only versions in requirements.txt - **Permission errors**: Check file permissions - **Memory issues**: Reduce chunk_size in config.json ## Next Steps 1. Read the full [README.md](README.md) for detailed documentation 2. Configure your MCP client to use this server 3. Add your documents to the vector store 4. Start searching and processing documents! ## Support - Check the troubleshooting section in README.md - Ensure all dependencies are installed - Verify Python version (3.8+) - Check system resources (RAM, disk space)