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"Chat with RAG (Retrieval-Augmented Generation)" matching MCP servers:

  • MCP RAG with ChromaDB

    CyprianFusi
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    Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.
    Last updated
    1
    MIT

  • Knowledge Retrieval Server

    cskwork
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    A BM25-based MCP server that enables document search and retrieval across structured domains of knowledge content, allowing Claude to search and reference documentation when answering questions.
    Last updated
    4
    1

  • MCP-RAG Server

    apatoliya
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    A server that implements Retrieval-Augmented Generation using GroundX and OpenAI, enabling semantic search and document retrieval with Modern Context Processing for enhanced context handling.
    Last updated
    3

  • PDF RAG MCP Server

    abdellahiheiballa
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    A Model Context Protocol (MCP) server that provides powerful RAG (Retrieval-Augmented Generation) capabilities for PDF documents. This server uses ChromaDB for vector storage, sentence-transformers for embeddings, and semantic chunking for intelligent text segmentation.
    Last updated
    MIT

  • RAG-MCP Server

    plaban1981
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    A server that integrates Retrieval-Augmented Generation (RAG) with the Model Control Protocol (MCP) to provide web search capabilities and document analysis for AI assistants.
    Last updated
    4
    Apache 2.0

  • mcp-rag-server

    kwanLeeFrmVi
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    An MCP server that indexes documents and serves relevant context to LLMs via Retrieval Augmented Generation (RAG).
    Last updated
    37
    36
    MIT

  • OmniDocs RAG

    ElvinBayramov
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    Enables AI agents to index and search local files, websites, GitHub repos, and packages using hybrid retrieval with reranking, all through IDE chat.
    Last updated
    4
    Apache 2.0

  • mcp-rag-server

    shabib87
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    A Model Context Protocol (MCP) server with Retrieval-Augmented Generation (RAG) for answering questions about imaginary SuperNova documentation. Enables semantic search over documentation using HuggingFace embeddings.
    Last updated
    1
    MIT

  • Modular RAG MCP Server

    VirtualCoder0
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    A modular RAG (Retrieval-Augmented Generation) service framework with pluggable architecture and full observability, enabling AI assistants to perform document Q\&A, semantic search, and knowledge base construction through the Model Context Protocol.
    Last updated
    MIT

  • mcp-rag-server

    FORIFOR
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    MCP RAG Server is a Python MCP server that indexes documents in multiple formats (Markdown, text, PowerPoint, PDF) using multilingual-e5-large embeddings and enables vector search for retrieval-augmented generation.
    Last updated
    MIT

  • google-chat-mcp

    yashasawarokt
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    An MCP server that connects Claude to your Google Chat workspace, enabling search of messages, spaces, and DMs with automatic resolution of real display names.
    Last updated
    MIT

  • RAG MCP Server

    torkian
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    Enables Claude Desktop to search custom knowledge bases using retrieval-augmented generation via a simple MCP tool.
    Last updated
    MIT

  • MCP RAG Server

    karaage0703
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    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.
    Last updated
    71
    MIT

  • Chat Context MCP

    aolshaun
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    Enables AI to automatically search, retrieve, and organize your Cursor chat history across sessions. Supports tagging, nicknames, project-scoped search, and full-text search to maintain context between conversations.
    Last updated

  • RooCode-RAG-Lookup

    Mazchoo
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    Enables semantic search across documents and code repositories using RAG (Retrieval-Augmented Generation) with vector embeddings. Automatically indexes PDF documents and performs relevance-scored lookups through ChromaDB and sentence transformers.
    Last updated