Provides RAG (Retrieval Augmented Generation) access to technical documentation through MCP, enabling LLMs to search and retrieve relevant documentation on-demand.
Enables document ingestion, semantic search, and retrieval-augmented generation via MCP tools and REST API, using vector embeddings and intelligent chunking.
Enables local document question-answering and retrieval via MCP, supporting multi-turn conversation, intent recognition, and tools for document search, Q&A, and summarization.
MCP server that enables querying an HR FAQ document via RAG, returning accurate answers and related chunks, and supports index rebuilding and response evaluation.