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"namespace:com.apple-rag" matching MCP servers:

  • RAG Anything MCP Server

    jesse-merhi
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    An MCP server that provides comprehensive multimodal Retrieval-Augmented Generation (RAG) capabilities for processing and querying document directories, supporting text, images, tables, and equations.
    Last updated
    19
    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

    sourangshupal
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    Implements Retrieval-Augmented Generation (RAG) using GroundX and OpenAI, allowing users to ingest documents and perform semantic searches with advanced context handling through Modern Context Processing (MCP).
    Last updated
    5
    • Linux
    • Apple

  • Crawl4AI RAG MCP Server

    coleam00
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    Web crawling and RAG implementation that enables AI agents to scrape websites and perform semantic search over the crawled content, storing everything in Supabase for persistent knowledge retrieval.
    Last updated
    2,141
    MIT
    • Linux
    • Apple

  • py-mcp-qdrant-rag

    amornpan
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    Enables semantic search and retrieval-augmented generation (RAG) using Qdrant vector database. Supports indexing documents from URLs and local directories, with flexible embedding options using Ollama or OpenAI.
    Last updated
    2
    • Apple
    • Linux

  • RAG MCP Server

    ali-48
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    Combines a knowledge graph with RAG (Retrieval-Augmented Generation) capabilities for semantic code indexing and search. Enables creating entity relationships, managing observations, and performing semantic searches across indexed codebases.
    Last updated
    13

  • 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

  • RAG Database MCP Server

    Human-center
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    Enables AI assistants to search and query PDF documents through a local RAG system with vector embeddings. Provides semantic document search capabilities while keeping all data stored locally without external dependencies.
    Last updated
    • Apple
    • Linux

  • MCP-RAG Server

    felixscherz
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    Connects a RAG application to open-webui using Model Context Protocol (MCP), enabling server-to-client communication for context retrieval and tool usage in remote environments through Server-Sent Events (SSE).
    Last updated
    1

  • RAG GroundX MCP Server

    Geoffrey-42
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    Enables advanced semantic search and document management by integrating the GroundX API with Claude Desktop and GitHub Copilot. It supports local file uploads, website crawling, and Google Drive synchronization for RAG workflows.
    Last updated
    1
    MIT

  • Cocktails RAG MCP Server

    00200200
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    Provides cocktail recommendations using a Retrieval-Augmented Generation (RAG) pipeline powered by LangChain, FAISS, and Groq. It enables users to search for cocktail recipes and receive personalized drink suggestions through natural language.
    Last updated
    • Apple

  • Calibre RAG MCP Server

    ispyridis
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    Enables semantic search and contextual conversations with your Calibre ebook library using vector-based RAG technology. Supports project-based organization, multi-format book processing, and OCR capabilities for enhanced content extraction and retrieval.
    Last updated
    7
    2

  • Lenny RAG MCP Server

    mpnikhil
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    Provides hierarchical RAG over 299 Lenny Rachitsky podcast transcripts for product development brainstorming and insight retrieval. It enables semantic search across topics, insights, and examples to surface expert advice on product management and growth.
    Last updated
    5

  • MCP RAG Server

    LuizDoPc
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    Provides local Retrieval-Augmented Generation (RAG) capabilities using Ollama for embeddings and ChromaDB for vector storage. It enables users to ingest and perform semantic searches across PDF, Markdown, and TXT documents within MCP-compatible clients.
    Last updated
    4
    10
    1

  • Gemini CLI RAG MCP

    pedarias
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    Transforms static gemini-cli documentation into a queryable RAG service, enabling developers to ask questions about Gemini CLI in natural language and receive instant, accurate answers based on the official documentation directly within their workflow.
    Last updated
    8
    MIT

  • 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
    MIT
    • Apple

  • 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
    70
    MIT

  • Modular RAG MCP Server

    yj-liuzepeng
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    A pluggable and observable modular RAG framework that enables AI assistants to perform semantic search, document Q\&A, and knowledge base retrieval. It supports hybrid search, reranking, and multiple LLM backends through a standardized Model Context Protocol interface.
    Last updated
    8
    • Apple
    • Linux

  • Hybrid RAG MCP Server

    jiarongli517021911144
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    A modular Retrieval-Augmented Generation (RAG) framework that provides hybrid search and knowledge retrieval capabilities via the Model Context Protocol. It enables users to integrate document-based knowledge into LLM workflows with support for dense/sparse retrieval, reranking, and observability.
    Last updated

  • local-RAG-backend

    suwa-sh
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    A Docker-based local RAG backend that provides advanced document search capabilities using vector, graph, and full-text retrieval via the Model Context Protocol. It supports over 28 file formats and tracks evolving relationships between concepts using a Neo4j-backed graphiti implementation.
    Last updated
    1
    MIT

  • RAG MCP Tool

    musnows
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    Provides intelligent retrieval capabilities for local files by scanning directories, generating vector indexes, and enabling semantic search through RAG (Retrieval Augmented Generation) with incremental indexing support.
    Last updated
    2

  • Crawl4AI RAG MCP Server

    Chillbruhhh
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    Provides AI agents and coding assistants with advanced web crawling and RAG capabilities, allowing them to scrape websites and leverage that knowledge through various retrieval strategies.
    Last updated
    2
    MIT
    • Apple
    • Linux

  • Godot RAG MCP Server

    weekitmo
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    Provides access to Godot engine documentation through a Retrieval-Augmented Generation (RAG) system using ChromaDB. It enables users to query processed Godot documentation and technical chunks for development assistance within MCP-compatible environments.
    Last updated
    25
    MIT

  • ZIM RAG MCP Server

    gglessner
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    Enables interaction with .zim archives by providing tools for article search, content retrieval, and metadata discovery. It features a TF-IDF based RAG engine for semantic retrieval over extracted article chunks from compressed ZIM files.
    Last updated
  • SOLVRO MCP - Knowledge Graph RAG System by Solvro

    SOLVRO MCP - Knowledge Graphofficial

    Solvro
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    Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.
    Last updated
    5

  • Documentation Fetcher & RAG

    mikkelkrogsholm
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    Enables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.
    Last updated

  • Apple RAG MCP

    devbifta
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    Provides AI agents with instant access to official Apple developer documentation, Swift programming guides, design guidelines, and Apple Developer YouTube content including WWDC sessions. Uses advanced RAG technology with semantic search and AI reranking to deliver accurate, contextual answers for Apple platform development.
    Last updated
    7