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    Aggregates and analyzes fitness data from multiple sources like Whoop and Strava through a modular adapter architecture. It enables users to monitor health metrics, track activities, and gain insights into sleep, recovery, and training performance.
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    MIT
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    Local MCP server that connects Claude Desktop with Garmin and Apple Health data to read training and recovery, estimate heart rate and pace zones, analyze performance, and create structured workouts.
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    MIT
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    Enables AI assistants to manage recipes, meal plans, and shopping lists in Mealie through natural language, supporting CRUD operations and URL-based recipe imports.
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    MIT
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    Enables AI assistants to access and analyze intervals.icu training data including activities, fitness metrics (CTL/ATL/TSB), wellness stats, and calendar events. Supports natural language querying of athletic performance for training insights and workout planning.
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    A Model Context Protocol (MCP) server for Intervals.icu integration. Access your training data, wellness metrics, and performance analysis through Claude and other LLMs.
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    MIT
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    Integrates with the Strava API to allow AI assistants to access fitness data including athlete profiles, activity history, and segment statistics. It enables users to query detailed performance metrics and explore geographic segment data through natural language commands.
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    108
    MIT
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    Connects Claude to the Strava API to provide direct access to fitness data, including athlete statistics, detailed activity logs, and time-series performance metrics. It enables users to analyze training progress, compare workouts, and retrieve specific segment details through natural language queries.
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    ISC
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    A Model Context Protocol server that integrates Garmin Connect data with LLMs to provide personalized running analysis and training plans. It enables users to monitor performance metrics, manage training loads, and receive data-driven workout suggestions based on health indicators like VO2 Max and recovery status.
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    Connect AI assistants to your Baby Buddy instance to log and query feedings, sleep, diaper changes, and more.
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    BSD 2-Clause "Simplified"
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    Provides comprehensive access to Strava API for marathon training and race analysis, enabling language models to query athlete data, analyze training patterns, track performance metrics, monitor heart rate zones, and detect injury risks.
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    MIT
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    A Python-based Model Context Protocol server that provides AI assistants with access to Oura Ring health and fitness data across 15+ endpoints. It enables querying metrics like sleep, activity, readiness, and cardiovascular health through simple authentication and date-range filtering.
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    MIT
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    Enables AI-driven weekly meal planning with structured recipes, cooking steps, and grocery lists.
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    MIT