"A guide to storyboarding or creating storyboards" matching MCP servers:

Enables workout tracking and coaching within Claude conversations, managing exercise configs, logs, streaks, and health metrics via an MCP server with PostgreSQL.

Exposes Garmin Connect health and activity data (steps, sleep, heart rate, etc.) via MCP tools, with built-in login and MFA support.

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.

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.

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.

A stateless MCP server that normalizes strength training logs into a deterministic canonical schema, enabling consumers to build analytics downstream without storing data server-side.

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.

A read-only MCP server that gives Claude Desktop access to your Garmin Connect data — daily health metrics, sleep, activities, training status, and body composition.

Enables LLM clients to read a user's locally-decrypted calisthenics training data and propose plan updates without direct mutations.

Enables an LLM to search a movement library, log single-movement and multi-movement workout results, and pull complete logged training history plus PR trends for Beyond the Whiteboard straight from a chat. All logged entries are posted privately, and session authentication can refresh automatically.

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.

A local-first, read-only MCP server that provides compact recovery, sleep, strain, HRV, heart-rate, workout, and body-measurement data from WHOOP without sending credentials to a third party.

Enables agents to read Mi Band health records from a computer, providing recent status, daily reports, historical details, and data sync via Gadgetbridge and USB, with agent-guided setup.

Provides a unified MCP interface to a personal health database, enabling AI agents to sync lifting workouts from Hevy, log food intake against a catalog, and run read-only SQL queries to cross-reference training and nutrition data.

Brings Garmin training data into Claude via Intervals.icu, enabling querying of activities, wellness, and planned workouts, as well as creating structured workouts that sync back to the Garmin watch.

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.

MCP server for reading and querying Garmin Connect data, including activities, strength history, recovery, trends, and optionally creating workouts.

Enables users to access and query Oura ring health data, including sleep periods, readiness, activity, workouts, heart rate, stress, SpO2, resilience, and more, through Claude.ai or Claude Code using the Oura API v2 with OAuth 2.1 login.

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.

Enables AI agents to sync WHOOP recovery, sleep, workouts, cycles, and body-measurement data into a local Postgres database and query it through fast, offline-capable MCP tools without repeatedly hitting WHOOP API rate limits.