Exposes a RAG document-search API as MCP tools (rag_health, rag_ingest, rag_query), enabling agents to index and search markdown documents with cited results through natural language.
Exposes a Retrieval-Augmented Generation pipeline as MCP tools, allowing users to index documents and query them through any MCP-compatible client like Claude or IDEs.
Provides tools for ingesting documents into a local vector database and retrieving relevant information via semantic search, enabling retrieval-augmented generation for MCP clients.
Provides read-only MCP tools for searching and asking over private documents via a local RAG service (reed), returning ranked passages with citations while keeping data on the machine.
A local-first document retrieval engine that mounts as an MCP tool for agents to index files, search for relevant passages, and let the agent's own LLM answer.