pdf-rag-mcp-server
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A powerful document knowledge base system that leverages PDF processing, vector storage, and MCP (Model Context Protocol) to provide semantic search capabilities for PDF documents.
The PDF RAG MCP Server is a comprehensive system designed to manage and query PDF documents using advanced technologies like vector storage and the Model Context Protocol (MCP). It allows users to upload, process, and search PDF documents through a modern web interface or integrate with AI tools like Cursor via the MCP protocol. The system is built on a FastAPI backend that handles API requests, PDF processing, and vector storage, while a React frontend offers a user-friendly interface for document management. Real-time processing updates are provided through a WebSocket server, and the MCP server exposes the knowledge base to MCP-compatible clients. This setup ensures efficient document management and retrieval, making it an ideal solution for organizations looking to leverage their PDF data effectively.
Features
- PDF Document Upload & Processing: Upload PDFs and automatically extract, chunk, and vectorize content.
- Real-time Processing Status: WebSocket-based real-time status updates during document processing.
- Semantic Search: Vector-based semantic search across all processed documents.
- MCP Protocol Support: Integrate with AI tools like Cursor using the Model Context Protocol.
- Modern Web Interface: React/Chakra UI frontend for document management and querying.
Tools
Cursor
An AI tool that can integrate with the PDF RAG MCP Server using the MCP protocol.