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"Kotlin RAG (Retrieval-Augmented Generation) implementation resources" matching MCP servers:

  • Retrieval-Augmented Thinking

    stat-guy
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    Enhances AI model capabilities with structured, retrieval-augmented thinking processes that enable dynamic thought chains, parallel exploration paths, and recursive refinement cycles for improved reasoning.
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    22
    MIT
    • Apple

  • Kotlin MCP Server

    normaltusker
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    Kotlin MCP Server for Android app development using OpenAI, Gemini, or OpenRouter. Enables AI-assisted coding via Aider, Gradle build/test integration, Kotlin LSP, and Docker-based portability.
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    28
    AGPL 3.0
    • Linux
    • Apple

  • 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

    AnuragB7
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    An MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.
    Last updated
    9
    MIT

  • 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

  • Markdown RAG

    ashrobertsdragon
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    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.
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    1

  • 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.
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    4
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  • MCP RAG

    santis84
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    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.
    Last updated
    11
    8
    1
    MIT

  • 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.
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    3
    • Linux
    • Apple

  • 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.
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  • 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

  • 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

  • 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

    NSANTRA
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    Enables Claude to perform retrieval-augmented generation using LangChain, ChromaDB, and HuggingFace models for domain-aware reasoning with PDF embedding, smart retrieval, reranking, and citation-based responses.
    Last updated
    2
    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

  • RAG-MCP

    Luxter77
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    A Python server that enables retrieval-augmented generation through semantic, question/answer, and style search modalities using PostgreSQL and pgvector for embedding storage and retrieval.
    Last updated
    2
    Apache 2.0

  • RAG MCP Server

    Alex-ChanHC
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    A Model Context Protocol server that exposes Retrieval-Augmented Generation capabilities and a weather tool, allowing clients to interact with document knowledge bases and retrieve weather information.
    Last updated
    • Apple
    • Linux

  • 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.
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    2
    • Apple
    • Linux

  • Kedro RAG MCP

    SajidAlamQB
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    An MCP server that enables users to query Kedro framework documentation using retrieval-augmented generation. It builds a local knowledge base from documentation files to help users navigate and apply Kedro's data science pipeline framework.
    Last updated
    • Apple

  • 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

  • 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

  • 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

  • MCP RAG

    kalicyh
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    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.
    Last updated
    10
    5

  • MCP-RAG

    ANSH-RIYAL
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    An agentic AI system that orchestrates multiple specialized AI tools to perform business analytics and knowledge retrieval, allowing users to analyze data and access business information through natural language queries.
    Last updated
    3

  • 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

  • MCP Enhanced Data Retrieval

    kalpalathika
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    Enables AI applications to access and contextualize organizational knowledge sources including GitHub repositories and internal documentation through standardized MCP protocol integration. Features OAuth 2.1 authentication, vector-based semantic search, and optimized context chunking for enterprise development workflows.
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  • 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

  • MCP-RAG

    seanshin0214
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    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.
    Last updated
    8
    MIT
    • Apple
    • Linux

  • glowfic-rag

    keenanpepper
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    Provides semantic search capabilities over glowfic.com content using a pre-built vector database and GTE-Large embeddings. It allows users to query specific continuities and authors through MCP-compatible tools in applications like Claude Code and Cursor.
    Last updated

  • 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

  • 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