Enables AI tools to securely search and retrieve relevant, source-attributed chunks from private local documents via MCP, without sending document content to third-party services.
An MCP server that enables Claude Desktop or Claude Code to ingest and search local documents using vector embeddings, returning relevant chunks as tool results for the model to reason over.
Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.
Enables fully local retrieval over a personal document corpus via hybrid search, cross-encoder reranking, RAPTOR summaries, and knowledge graph queries, served to AI agents over MCP.
Provides persistent long-term memory and local RAG document search for Claude Desktop, fully offline. Enables memory save/search and document retrieval via MCP.