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    A local MCP server that caches Garmin Connect data in SQLite for fast, read-only queries, with tools for bulk import, rate-limited sync, and failure alerts.
    9
    MIT
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    Provides access to the Nutrition By Api Ninjas API to extract detailed nutritional information from natural language food queries. It enables users to retrieve data such as calories, vitamins, and macros from text descriptions of meals.
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    MIT
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    MCP server for workout-file conversion: convert, validate, and inspect FIT, TCX, ZWO, and Garmin Connect files, with round-trip-safe conversions through the KRD canonical JSON format. Runs locally over stdio via npx -y @kaiord/mcp. Part of the open-source, local-first Kaiord training platform.
    9
    MIT
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    Enables AI assistants to search and retrieve Narcotics Anonymous meeting information from the BMLT database, supporting queries by location, time, format, and service body.
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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.
    9
    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.
    10
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    MIT
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    Enables browsing the Ptitchef recipe category tree and reading its recipes without an API key or account.
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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.
    3
    MIT
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    Enables AI assistants to read your SisRUN training plan with your own credentials and answer questions about prescribed workouts, like weekly coach plans, in a structured format.
    3
    MIT
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    Enables Claude to read your WHOOP health data including recovery, sleep, strain, and workouts through the official WHOOP API, so you can ask natural language questions about your fitness metrics.
    7