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  • Plesk Extensions Guide MCP

    barateza
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    Provides semantic search capabilities over the Plesk Extensions Guide documentation using Retrieval-Augmented Generation (RAG) and vector embeddings. It enables AI assistants to retrieve relevant technical information and answer natural language queries regarding Plesk extension development.
    Last updated

  • Agentic RAG MCP

    enached134-ctrl
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    A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.
    Last updated
    3
    1
    MIT

  • mem-context

    turbyho
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    Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.
    Last updated
    10
    MIT

  • velesdb-memory

    cyberlife-coder
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    Local-first agent-memory MCP server with a why() tool: recall a fact together with its connected subgraph (multi-hop), so linked memories surface even when they share no words with the query. remember/recall/relate/forget/why over one fused vector + graph + columnar engine a single offline Rust binary.
    Last updated
    8
    79

  • XMemo

    yonro
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    XMemo is a secure, user-owned memory substrate and context engine for AI agents, CLIs, IDEs, and LLM workspaces. Exposed over Streamable HTTP MCP, it empowers agents with cross-session memory, task continuity, and personalized context. Key Features: * Personalized Context: Stores and recalls developer preferences, project guidelines, and coding patterns via semantic vector search. * Agent Daily Me
    Last updated
    20
    480
    12
    MIT

  • 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

  • MCP-Markdown-RAG

    Zackriya-Solutions
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    A Model Context Protocol (MCP) server that provides a local-first RAG engine for your markdown documents. It uses a file-based Milvus vector database to index your notes, enabling LLMs to perform semantic search and retrieve relevant content from your local files.
    Last updated
    55
    Apache 2.0

  • RAG-MCP Knowledge Base Server

    Luxter77
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    Enables semantic search across text documents using vector embeddings stored in PostgreSQL. Provides multiple search modalities including semantic similarity, question/answer, and style-based search through a retrieval-augmented generation system.
    Last updated
    3
    Apache 2.0

  • KuzuMem-MCP

    Jakedismo
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    A distributed memory bank MCP server that stores AI agent memories in a KùzuDB graph database with repository/branch isolation. Features AI-powered memory optimization, dependency tracking, and comprehensive graph analysis capabilities.
    Last updated
    25

  • Prompt Learning MCP Server

    curiositech
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    Provides stateful prompt optimization using research-backed techniques like APE and OPRO, learning from historical performance data via a vector database. It enables users to automatically refine prompts, retrieve high-performing examples, and track performance analytics through iterative feedback.
    Last updated
    3

  • ChatPPT-MCP

    pingcy
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    quality
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    A multi-document RAG engine server that enables intelligent querying and analysis of PPT documents using the Model Context Protocol (MCP).
    Last updated
    12