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"How to allow an LLM to ask questions to a user" matching MCP servers:

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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.
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    Enables Claude to access and analyze Suunto sports watch data, allowing users to ask natural-language questions about their workouts, training metrics, and history.
    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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    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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    MCP server to read daily activity, sleep, heart rate, and body metrics from Google Health API, allowing AI assistants like Claude to access your health data. Optionally syncs health metrics to an Obsidian vault.
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    MIT
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    MCP server that connects Claude or any MCP-capable LLM to your Garmin golf data, enabling natural-language queries on rounds, shots, strokes gained, club distances, course intel, and health-performance correlations from a private local DuckDB cache.
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    MIT
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    Enables AI assistants to answer questions about and log a user's FitTrack fitness data after validating a short-lived personal access token, with tools like recent_workouts and today_nutrition.
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    A local-first MCP server that enables AI agents to read user-authorized Google Health API v4 data from Fitbit, Pixel Watch, and partners via OAuth, with tokens never leaving the machine.
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    MIT
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    A TypeScript server that acts as a bridge to the Strava API, enabling LLMs to access users' activities, routes, segments, and athlete data through natural language interaction.
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    MIT
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    MCP server for the Withings Health API with per-user OAuth2, enabling users to securely access their own health data (measures, activity, sleep, workouts, heart rate, devices, and goals) and optionally add measurements.
    12
    Apache 2.0
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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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    MIT
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    A production-ready MCP server for the Hevy fitness API that exposes 27 tools for reading, writing, and analyzing workout data, enabling LLM-driven personal trainer workflows.
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    MIT
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    MacroFactor MCP is a local Fueling & Recovery Decision Engine. Give your MCP client a MacroFactor export, optionally add Garmin, and ask for a decision instead of manually comparing nutrition, sleep, body, and training screens.
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    MIT
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    Enables access to WHOOP fitness and health data through all WHOOP v2 API endpoints. Supports OAuth 2.0 authentication and provides comprehensive access to user profiles, physiological cycles, recovery metrics, sleep analysis, and workout data.
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    MIT