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"Exploring RAG through defined workspaces" matching MCP servers:

  • knowledge-rag

    lyonzin
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    license
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    quality
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    maintenance
    Local RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.
    13
    252
    MIT

  • rag-mcp

    NextLevelManagementAdvisors
    A
    license
    A
    quality
    B
    maintenance
    Enables ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.
    4
    AGPL 3.0

  • MCP RAG

    kalicyh
    F
    license
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    quality
    C
    maintenance
    Intelligent knowledge base system that enables users to process documents in 25+ formats, perform semantic search and Q\&A through vector retrieval. Supports multiple AI models including OpenAI and DouBao with local processing capabilities.
    10
    6

  • MCP RAG

    santis84
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    license
    B
    quality
    D
    maintenance
    A complete MCP server for Retrieval-Augmented Generation with file management and vector memory for agents. Supports multiple document formats (PDF, DOCX, TXT, MD, CSV, JSON) with semantic search using Hugging Face embeddings and ChromaDB for efficient vector storage.
    11
    13
    1
    MIT

  • Markdown RAG

    ashrobertsdragon
    A
    license
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    quality
    D
    maintenance
    A Retrieval Augmented Generation system that enables AI assistants to perform semantic searches and manage document indices for markdown files. It supports PostgreSQL with pgvector and integrates both Google Gemini and Ollama for intelligent embedding generation.
    1
    MIT

  • local-rag-mcp

    Orax0001
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    license
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    quality
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    maintenance
    A privacy-preserving local RAG system integrated with MCP, enabling natural language queries over ingested documents and a SQLite database through vector search and local database tools.
    MIT

  • RAG Memory MCP

    ttommyth
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    license
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    quality
    C
    maintenance
    An advanced MCP server providing RAG-enabled memory through a knowledge graph with vector search capabilities, enabling intelligent information storage, semantic retrieval, and document processing.
    123
    47
    MIT

  • MCP-RAG

    AnuragB7
    A
    license
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    quality
    C
    maintenance
    An MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.
    10
    MIT

  • MCP RAG Server

    karaage0703
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    license
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    quality
    D
    maintenance
    Enables retrieval-augmented generation (RAG) by indexing and searching through documents (Markdown, text, PowerPoint, PDF) using vector embeddings with multilingual-e5-large model and PostgreSQL pgvector. Supports contextual chunk retrieval and incremental indexing for efficient document management.
    71
    MIT

  • RAG MCP Server

    sglwsjxh
    A
    license
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    quality
    A
    maintenance
    A RAG knowledge base MCP server that adds vector search and reranking capabilities to opencode, supporting multimodal embeddings, multiple knowledge bases, and local storage.
    1
    MIT

  • MCP-RAG

    seanshin0214
    A
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    quality
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    maintenance
    Turns Claude Desktop into a personal document question-answering system using local vector search. Index PDF, TXT, and Markdown documents into collections and get answers based strictly on your documents with zero hallucination.
    13

  • RAG-MCP

    alejandro-ao
    F
    license
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    quality
    D
    maintenance
    A Retrieval Augmented Generation MCP server that ingests documents into a local vector database and enables semantic search queries.
    10

  • rag-server

    andreeagheorghe
    F
    license
    -
    quality
    B
    maintenance
    Local MCP server that provides a search_documents tool to query a RAG pipeline built with Ollama embeddings and ChromaDB, enabling Claude Desktop to retrieve relevant document chunks.