RAG Large File Processor
Processes large documents in multiple formats using intelligent chunking and advanced retrieval-augmented generation (RAG) capabilities.
About
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.
Key Features
- 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
Use Cases
- 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.
Sponsored