"Handling Sketch File Context and SVG Processing Overview" 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 MCP clients to query read-only Oura health data—readiness, sleep, HRV, activity, stress, heart rate and tags—through combined daily overviews, multi-day trends and aggregated heart-rate series. Authentication stays local via OAuth with PKCE, graceful handling of unavailable data types, and an optional sandbox of public sample data.

Provides Claude with real-time access to local health data including sleep, recovery, strain, and workouts from WHOOP and Apple Health, enabling informed context-aware interactions.

Enables AI assistants to access and analyze Polar device health data, including exercises, heart rate, sleep, and recovery metrics, by preprocessing raw sensor data into compact summaries to avoid context window overload.

A Model Context Protocol server for TrainingPeaks with an analytics focus — enabling real-time querying of training data, performance trends, CTL/ATL/TSB analysis, and training load optimization through Claude Desktop.

Enables MCP clients to query AimHarder for authenticated account context, discover accessible gyms, and select a gym for queries.

Exposes real-time health data from the Ultrahuman Ring to AI agents via the Model Context Protocol, providing optimized summaries with trend analysis and actionable insights.

A Model Context Protocol (MCP) server for Garmin Connect integration. Access your activities, health data, training metrics, and more through Claude and other LLMs.

Enables read-only querying of your own Garmin Connect data — sleep, HRV, resting HR, Body Battery, activities, training volume, body composition, and nutrition — through Garmin's official Personal API using a revocable key. Returns compact, unit-labelled JSON shaped around questions so whole date ranges fit in context.

Connects Sensor Bio wearable data to AI assistants via the Model Context Protocol, enabling queries about sleep, heart rate, activity, and other biometrics.

A lightweight Garmin Model Context Protocol server with 12 curated endpoints for endurance athletes, enabling natural-language queries of activity, training, health, device, and goal data from Garmin Connect.

An MCP server for authoring and managing structured workouts (SuuntoPlus™ Guides) on Suunto watches, with swappable transports (file, Cloud API, or private mobile API) and a coach-oriented domain model that lowers to the display-oriented guide format.

A Model Context Protocol server that connects Claude to Hevy workout logs, enabling workout reading, routine creation, and training analysis.

A Model Context Protocol (MCP) server implementation that interfaces with the Hevy fitness tracking app and its API. This server enables AI assistants to access and manage workout data, routines, exercise templates, and more through the Hevy API (requires PRO subscription).

Enables agents to locally analyze Huawei Health export data, retrieve activity summaries, tracks, samples, and health context, and generate structured report evidence with optional environmental data.

A Model Context Protocol (MCP) server that fetches sleep, HRV, and training data from the unofficial Coros API and exposes them to AI assistants like Claude, enabling natural language queries about fitness metrics and workout management.

Local-first cycle coach MCP for phase-aware nutrition and training context.

A Model Context Protocol (MCP) server for Intervals.icu integration. Access your training data, wellness metrics, and performance analysis through Claude and other LLMs.

A Model Context Protocol (MCP) server that provides comprehensive access to Garmin Connect data including sleep analytics, health metrics, activities, and training volume analysis.