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Build a local AI Q&A system using RAG and MCP

This guide details how to build a local question-and-answer system capable of querying personal documents like PDFs and spreadsheets. It leverages Retrieval Augmented Generation (RAG) combined with the Model Context Protocol (MCP) to create a modular pipeline. The system will consist of three services: a document ingestion server, an MCP tool server, and a conversational AI agent powered by LangChain. AI

IMPACT Enables users to build custom, local AI assistants for querying private documents, enhancing productivity.

RANK_REASON Article describes a practical implementation of existing AI techniques for a specific use case.

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Build a local AI Q&A system using RAG and MCP

COVERAGE [1]

  1. dev.to — MCP tag TIER_1 English(EN) · David Archanjo ·

    Chat with Your Docs: Working with LangChain, RAG, MCP, ChromaDB Made Simple

    <p>Have you ever wished you could ask questions from a pile of documents, spreadsheets, or PDFs sitting on your machine and <em>magically</em> get answered? It's not magic and in this guide, we will build exactly that: <em>a local Q&amp;A system that lets we chat with your docume…