"A design and prototyping tool for user interface and user experience (UI/UX) design" matching MCP servers:

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

MCP server for tracking nutrition meals and workouts, integrating with claude.ai to manage food logs, macros, exercise catalogs, and generate daily/weekly summaries.

Enables Claude to act as a personal health coach by connecting to Garmin wearable data and Notion workspace for automated calorie tracking, photo food logging, and coaching insights.

An MCP server that connects Claude to intervals.icu training data, enabling advanced physiological analysis, activity and wellness management, and conversational insights using proprietary metrics like CCI and HRV correction.

Connects WHOOP fitness data to Poke AI assistant, enabling natural language queries for recovery scores, sleep analysis, strain tracking, and healthspan metrics.

MCP server that connects AI assistants like Claude to WHOOP health data, enabling natural language queries about recovery, sleep, workouts, and more.

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

Exposes over 90 Garmin Connect tools for tracking activities, health metrics, and training data through the Model Context Protocol. It is optimized for Poke compatibility and supports deployment to Render via HTTP.

Enables AI agents like Claude Desktop, Cursor, and VS Code to connect directly to COLMI R02/R03 and compatible smart rings over local Bluetooth LE, exposing tools for ring scanning, battery and firmware status, activity and sleep/recovery insights, real-time heart rate and SpO2 vitals, 3-axis motion sampling, clock sync, and physical LED blinking. Runs fully locally with no vendor cloud, accounts, or subscriptions.

A Model Context Protocol server that enables users to access Strava fitness data, including user activities, activity details, segments, and leaderboards through a structured API interface.

Unofficial MCP server for Hevy that lets AI assistants design training programs, create routines directly in your Hevy account, and analyze logged workouts.

A universal fitness intelligence layer for AI assistants like Claude, ChatGPT, and Copilot, enabling user profiles, workout/diet plans, calendar scheduling, and gamification via MCP and REST APIs.

A multi-user MCP server that exposes WHOOP fitness data (recovery, sleep, workouts, cycles, profile, body measurements) to AI clients. Each user connects their own WHOOP account via OAuth and only sees their own data, which is fetched live on every tool call.

A multi-user OAuth 2.1-protected gateway that enables Claude to access Garmin Connect tools through secure per-user sessions.

Enables Claude to access and analyze Whoop health data including recovery, sleep, strain, and workouts through a custom MCP connector.

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.

MCP server for the Google Health API: heart rate, activity, sleep, SpO2, HRV, ECG and irregular-rhythm notifications, read into a local SQLite cache for fast offline queries and trend analysis. OAuth 2.0 with automatic token refresh, incremental sync, a cache-only offline mode, and a doctor command that diagnoses a setup without spending quota.

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