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

  • Retrieval-Augmented Thinking

    stat-guy
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    quality
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    maintenance
    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.
    Last updated
    24
    MIT

  • rag-retrieval-mcp

    MaryamZi
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    Enables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.
    Last updated
    Apache 2.0

  • Kotlin MCP Server

    normaltusker
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    quality
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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.
    Last updated
    31
    AGPL 3.0

  • retrieval-lens

    Vbj1808
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    quality
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    maintenance
    A black-box flight recorder for RAG retrieval inside MCP agents. Logs what chunks the model saw, scores, sources, and rankings - so you can audit, replay, and diff retrieval runs after the fact.
    Last updated
    8
    4
    0
    1
    MIT
  • Robot Resources Router by robot-resources

    Robot Resources Routerofficial

    robot-resources
    A
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    quality
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    maintenance
    LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.
    Last updated
    38
    1
    MIT

  • MCP RAG Server

    LuizDoPc
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    quality
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    maintenance
    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
    29
    1
    MIT

  • MCP RAG

    santis84
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    quality
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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
    6
    1
    MIT

  • Knowledge Retrieval Server

    cskwork
    F
    license
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    quality
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    maintenance
    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
    F
    license
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    quality
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    maintenance
    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

  • RAG MCP Server

    ali-48
    F
    license
    C
    quality
    D
    maintenance
    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

  • Markdown RAG

    ashrobertsdragon
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    quality
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    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.
    Last updated
    1
    MIT

  • RAG-MCP Server

    plaban1981
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    quality
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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

    shabib87
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    quality
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    maintenance
    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