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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