关于
Knowledge RAG is a 100% local, privacy-first Retrieval-Augmented Generation (RAG) system designed for seamless integration with Claude Code via the Model Context Protocol (MCP). It allows users to augment Claude's capabilities by providing relevant context from their personal documents, including PDFs, Markdown, text, and code files. The system features a sophisticated hybrid search mechanism, combining semantic understanding with precise BM25 keyword matching using Reciprocal Rank Fusion (RRF), enhanced by smart keyword routing. All data processing occurs locally, ensuring privacy, and parallel embedding generation with ChromaDB provides fast and accurate context retrieval for AI models.
