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    Enables users to describe workouts in plain English and have them created as structured Garmin Connect workouts with pace, HR, power, cadence targets, and repeat blocks. Also provides full workout lifecycle management including listing, updating, deleting, and scheduling to the calendar.
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    35 npm
    MIT
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    Provides local MCP tools to query your own Xiaomi Mi Fitness health data (sleep, workouts, heart rate, etc.) stored in a local SQLite database, enabling AI assistants to access personal health records without exposing credentials.
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    AGPL 3.0
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    An MCP server that converts structured cycling workout specs into MyWhoosh .zwo and Garmin Connect workout files, with tools for validation, description, and rendering. It also includes skills for uploading workouts to both platforms.
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    MIT
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    MCP server that lets you ask questions about your Garmin training history in plain language. It ingests FIT files into DuckDB locally and exposes typed tools for analyzing activities, streams, and summaries.
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    MIT
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    Ask your Oura Ring about sleep, readiness, activity, stress and heart rate in ChatGPT or Claude, in any language. Read-only, 10 task-oriented tools; runs in a sandbox demo mode with no credentials.
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    Enables Claude Desktop to query and analyze diabetes data from Omnipod 5 and Glooko through natural language, providing clinical audit and triage insights such as time in range, trends, and bolus analysis.
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    MIT
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    Provides read-only access to Oura ring biometrics via the Oura API, enabling Claude to query daily summaries, sleep, readiness, stress, workouts, baselines, and heart rate data. Designed to complement a Strava connector for joint analysis of training and recovery.
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    MIT
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    Provides SQL access to the ANSES Ciqual French food composition database with nutritional data for over 3,000 foods. Supports full-text search and bilingual queries for comprehensive nutrition analysis.
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    MIT
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    Query Apple Health export data with an LLM via a semantic layer that avoids common data traps, enabling accurate natural-language queries about health metrics. Optionally imports CPAP therapy data for correlation.
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    MIT
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    Mock MCP server for pediatric CKD risk warning, enabling patient biochemical trend retrieval, deterministic risk rule evaluation, structured alert triggering, and clinical SOP lookup using simulated data.
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    MIT
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    Exposes the Oura API v2 as an MCP server with tools to query all 19 data collections (e.g., sleep, heartrate) with automatic pagination and explicit truncation warnings.
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    136 PyPI
    MIT
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    Enables AI assistants to interact with Intervals.icu fitness tracking and wellness data, allowing users to fetch, filter, and group activities or health metrics. It provides structured summaries of workouts and physical well-being through natural language queries.
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    Enables LLMs to retrieve verified macronutrient data (calories, protein, carbs, fat) for real ingredients and quantities from USDA FoodData Central, with structured caveats for uncertain matches.
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