Enables semantic search and question-answering over FAQ documents using RAG (Retrieval-Augmented Generation) with OpenAI embeddings and in-memory vector similarity.
Exposes a local RAG document index as MCP tools (ask, search, rebuild_index, status) for MCP clients like Claude Desktop and Claude Code to query your documents over stdio.
Enables LLM clients to query local markdown engineering documentation by indexing files into ChromaDB with Ollama embeddings and exposing a search_internal_docs tool over stdio, all offline and privacy-first.