Enables document ingestion, semantic search, and retrieval-augmented generation via MCP tools and REST API, using vector embeddings and intelligent chunking.
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 document search and retrieval using TF-IDF vector similarity across HTML and PDF files. Provides ingest, query, and vector store management capabilities through both HTTP API and MCP stdio interfaces.
Enables natural language queries on technical specifications and automated code compliance checks using local RAG with vector search, integrated via MCP.