MCP RAG Agent

Example Use Cases

• 1

  Hybrid semantic and keyword search over large document corpora.

• 2

  That require grounded, context-aware responses with minimized hallucinations.

• 3

  That benefit from modular tool integration via the Model Context Protocol.

Description

The MCP RAG Agent combines hybrid search techniques using vector and full-text search with MongoDB Atlas, grounded COSTAR prompting, and automated RAGAS-based evaluation to build reliable AI agents. It leverages MCP for modular tool integration and LangGraph for intelligent reasoning and retrieval. This system enables scalable, accurate, and contextually grounded question-answering over policy documents and supports comprehensive evaluation to ensure answer quality.