Enables users to build and query a private knowledge base by uploading documents, which are embedded and stored locally, then accessible via MCP for semantic search and retrieval.
Provides tools for ingesting documents into a local vector database and retrieving relevant information via semantic search, enabling retrieval-augmented generation for MCP clients.
Enables RAG (Retrieval-Augmented Generation) capabilities with document processing, vector storage, and intelligent Q\&A using OpenAI embeddings and semantic search.