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"A tool or method to manage projects and tasks in GitHub Projects" matching MCP servers:

  • Tiny Chat

    to-aoki
    A
    license
    D
    quality
    C
    maintenance
    A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.
    1
    2
    MIT

  • slack-indexed

    KanvaBhatia-Alaan
    F
    license
    A
    quality
    D
    maintenance
    An MCP server for semantic search and retrieval of indexed Slack messages stored in Qdrant using Cohere reranking via AWS Bedrock. It enables users to search through Slack history, retrieve full message threads, and access channel or user statistics through natural language.
    5

  • PaperMCP

    ATFfang
    A
    license
    -
    quality
    C
    maintenance
    A lightweight, local, multi-project isolated paper index server that provides dual retrieval (BM25 + dense vector) via MCP, enabling agents to search and manage paper collections across isolated projects.
    MIT

  • Qdrant RAG MCP Server

    ancoleman
    F
    license
    -
    quality
    D
    maintenance
    Enables context-aware semantic search across codebases using Qdrant vector database with intelligent GitHub issue resolution, Projects V2 management, and progressive context retrieval for 95%+ token reduction in AI-assisted development.
    9

  • job-search-mcp

    jsundquist
    F
    license
    A
    quality
    B
    maintenance
    An MCP server that retrieves resume/experience evidence relevant to a job description via vector RAG, and tracks fit-analysis results in a configurable tracking store (Notion or SQLite), with tools like match_job, push_to_tracker, and list_applications.
    3

  • @git-fabric/aiana

    git-fabric
    F
    license
    A
    quality
    -
    maintenance
    A composable semantic memory layer that provides cross-project recall and session context using Qdrant and OpenAI embeddings. It enables users to securely store, search, and manage persistent memories with built-in secret scrubbing for privacy.
    11

  • memsem

    WindSeries69
    A
    license
    A
    quality
    A
    maintenance
    Semantic memory MCP server that gives AI agents a self-writing, priority-based memory with local semantic search and automatic contradiction handling. It persists across sessions and projects, entirely on your machine.
    18
    2,791
    2
    MIT

  • Redis MCP Server

    Yuchenhui
    A
    license
    A
    quality
    D
    maintenance
    Enables AI agents to manage and search data in Redis using natural language. Supports hashes, lists, sets, sorted sets, streams, JSON, and vector search.
    44
    MIT
  • Redis MCP Server by redis

    Redis MCP Serverofficial

    redis
    A
    license
    B
    quality
    B
    maintenance
    The official Redis MCP Server is a natural language interface designed for agentic applications to efficiently manage and search data in Redis.
    53
    563
    MIT

  • MCP Memory Server

    iamjpsharma
    A
    license
    B
    quality
    D
    maintenance
    A persistent local vector memory server that allows users to store and search project-specific context using LanceDB and local embeddings. It enables MCP-compliant editors to maintain long-term memory across different projects without requiring external API keys.
    6
    1
    MIT

  • ChromaDB MCP Server

    scooby359
    F
    license
    B
    quality
    D
    maintenance
    Enables GitHub Copilot to query local ChromaDB instances to retrieve relevant documents and context for AI conversations. It allows users to search vector collections using natural language tools directly within VS Code.
    1

  • Markdown RAG

    ashrobertsdragon
    A
    license
    -
    quality
    D
    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.
    1
    MIT