RAG Large File Processor

关于

RAG Large File Processor (MCP-RAG) is a system designed to handle and process large files (up to 200MB) for retrieval-augmented generation. Leveraging the Model Context Protocol (MCP), it intelligently chunks documents, supports multiple file formats (PDF, DOCX, Excel, CSV, PPTX, and various images), and offers enterprise-grade reliability. The system features advanced RAG capabilities such as semantic search, cross-document queries, and source attribution, while also providing integrations for custom LLM endpoints and vector databases like ChromaDB and Milvus.

主要功能

• Semantic search with vector similarity and confidence scores
• Integrates with Model Context Protocol (MCP) for standardized AI-to-tool communication
• 2 GitHub stars
• Supports multi-format documents (PDF, DOCX, Excel, CSV, PPTX, Images)
• Adaptive chunking strategies for large file processing
• Offers batch processing and error recovery for enterprise readiness

使用案例

• Building a knowledge base from a collection of diverse document types.
• Processing large financial reports for semantic search and analysis.
• Analyzing extensive research papers across multiple formats.