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"A server for pulling health and fitness data from Apple Health, Garmin, and Whoop" matching MCP servers:

  • Apple Tools MCP

    sfls1397
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    Enables semantic search across Apple Mail, Messages, Calendar, and Contacts on macOS using natural language queries. All processing happens locally with privacy-first vector indexing for fast similarity search.
    Last updated

  • MCP Apple Notes

    Dingzeefs
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    A Model Context Protocol server that enables semantic search and retrieval of Apple Notes content, allowing AI assistants to access, search, and create notes using on-device embeddings.
    Last updated
    839
    2
    MIT

  • MCP Server for Milvus

    zilliztech
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    An integration server implementing the Model Context Protocol that enables LLM applications to interact with Milvus vector database functionality, allowing vector search, collection management, and data operations through natural language.
    Last updated
    237
    Apache 2.0

  • mcp-lancedb

    adiom-data
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    A Model Context Protocol (MCP) server that enables LLMs to interact directly the documents that they have on-disk through agentic RAG and hybrid search in LanceDB. Ask LLMs questions about the dataset as a whole or about specific documents.
    Last updated
    14
    78
    MIT

  • privateGPT MCP Server

    Fujitsu-AI
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    A server implementation that allows secure communication between MCP clients and privateGPT, enabling users to chat with privateGPT using knowledge bases and manage sources, groups, and users through a standardized Model Context Protocol.
    Last updated
    6
    MIT

  • Munin AI Memory

    3d-era
    F
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    quality
    A
    maintenance
    Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on developer productivity with: * Multi-Project Support: Isolate memories into separate "brains" (Context Cores). * GraphRAG: Automatically builds a knowledge graph from your context. * Sub-200ms Search: Blazing fast Hybrid & Semantic
    Last updated
    3

  • EyeLevel RAG MCP Server

    wannabidr
    F
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    maintenance
    A local Retrieval-Augmented Generation system that enables users to ingest markdown files into a FAISS-powered vector knowledge base for semantic search. It provides tools for document indexing and context retrieval to support informed LLM queries without external dependencies.
    Last updated

  • Typesense MCP Server

    avarant
    A
    license
    A
    quality
    C
    maintenance
    A server that enables vector and keyword search capabilities in Typesense databases through the Model Context Protocol, providing tools for collection management, document operations, and search functionality.
    Last updated
    14
    10
    MIT
  • Zilliz MCP Server by zilliztech

    Zilliz MCP Serverofficial

    zilliztech
    A
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    quality
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    Enables AI agents to interact with Milvus vector databases and Zilliz Cloud through natural language, allowing users to create clusters, manage collections, insert vector data, and perform semantic searches directly from their AI assistants.
    Last updated
    16
    34
    Apache 2.0

  • KB-MCP Server

    isshiki-dev
    F
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    A local-first knowledge base server that enables AI clients to store, retrieve, and manage documents using semantic search. Provides privacy-focused, offline-capable memory for AI assistants with tools for ingesting, querying, updating, and deleting knowledge.
    Last updated
    7
    18

  • CoderSwap MCP Server

    njlnaet
    F
    license
    A
    quality
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    maintenance
    Enables AI agents to autonomously create and manage topic-specific vector knowledge bases with end-to-end functionality including project creation, content ingestion from URLs, semantic search, and progress tracking. Provides a complete research workflow without exposing low-level APIs.
    Last updated
    8
    93

  • AGI MCP Server

    randyandrade
    F
    license
    B
    quality
    D
    maintenance
    Enables persistent memory for AI systems by providing tools for episodic, semantic, and procedural data storage through a vector-and-graph-enhanced database. It allows models to maintain long-term continuity using similarity search, thematic clustering, and identity tracking.
    Last updated
    24
    1