Calibre RAG MCP Server

Enhanced Calibre MCP server with RAG (Retrieval-Augmented Generation) capabilities for project-based vector search and contextual conversations.

Features

• RAG-Enhanced Search: Vector-based semantic search using FAISS and Transformers
• Project-Based Organization: Create isolated vector search projects for different contexts
• Multi-Format Support: Process books in various formats (EPUB, PDF, MOBI, etc.)
• OCR Capabilities: Extract text from images and scanned PDFs using Tesseract
• Advanced Text Processing: Natural language processing for better content understanding
• Windows Compatible: Designed specifically for Windows environments

Technologies Used

• Vector Search: FAISS for efficient similarity search
• Embeddings: Xenova Transformers for local embedding generation
• OCR: Tesseract for optical character recognition
• PDF Processing: Multiple PDF parsing libraries (pdf-parse, pdf-poppler, pdf2pic)
• Image Processing: Sharp for image manipulation
• NLP: Natural language processing with multiple libraries

Prerequisites

• Node.js >= 16.0.0
• Calibre installed on Windows
• ImageMagick (for enhanced image processing)
• Tesseract OCR (for text extraction from images)

Installation

1. Clone this repository:

git clone https://github.com/yourusername/calibre-rag-mcp-nodejs.git
cd calibre-rag-mcp-nodejs

2. Install dependencies:

npm install

3. Run setup (Windows):

setup.bat

Configuration

The server automatically detects your Calibre library location. For custom configurations, modify the settings in server.js.

Usage

Starting the Server

npm start

Available Tools

• search: Semantic search across your ebook library
• fetch: Retrieve specific content from books
• list_projects: List all RAG projects
• create_project: Create a new RAG project
• add_books_to_project: Add books to a project for vectorization
• search_project_context: Search within specific projects

Example MCP Configuration

Add to your MCP client configuration:

{
  "mcpServers": {
    "calibre-rag": {
      "command": "node",
      "args": ["path/to/calibre-rag-mcp-nodejs/server.js"]
    }
  }
}

Project Structure

calibre-rag-mcp-nodejs/
├── server.js              # Main MCP server
├── package.json           # Dependencies and scripts
├── setup.bat              # Windows setup script
├── test-*.js              # Various test files
├── projects/              # RAG projects storage
├── CONFIG.md              # Configuration documentation
├── USAGE_EXAMPLES.md      # Usage examples
└── QUICK_TEST.md          # Quick testing guide

Testing

Run the test suite:

npm test

Individual test files:

• test-enhanced-server.js - Enhanced server functionality
• test-ocr-full.js - OCR capabilities
• test-pdf-approaches.js - PDF processing
• test-enhanced-auto.js - Automated testing

Documentation

• Configuration Guide
• Usage Examples
• Quick Test Guide

Requirements

System Requirements

• Windows 10/11
• Node.js 16+
• Calibre installed
• At least 4GB RAM (8GB+ recommended for large libraries)

Optional Dependencies

• ImageMagick (for enhanced image processing)
• Tesseract OCR (for text extraction from scanned documents)

Troubleshooting

Common Issues

1. FAISS Installation: If FAISS fails to install, ensure you have proper build tools
2. Tesseract Not Found: Install Tesseract and add to PATH
3. Memory Issues: Reduce batch sizes for large document processing

Debug Mode

Enable verbose logging by setting environment variable:

set DEBUG=calibre-rag:*
npm start

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Submit a pull request

License

Licensed under the Apache License 2.0. See LICENSE file for details.

Support

For issues and questions, please open an issue on GitHub.

Changelog

v1.0.0

• Initial release with RAG capabilities
• Project-based vector search
• Multi-format document support
• OCR integration
• Windows optimization