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

2. Install dependencies:
```bash
npm install
```

3. Run setup (Windows):
```bash
setup.bat
```

## Configuration

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

## Usage

### Starting the Server

```bash
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:

```json
{
  "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:

```bash
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](CONFIG.md)
- [Usage Examples](USAGE_EXAMPLES.md)
- [Quick Test Guide](QUICK_TEST.md)

## 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:
```bash
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