"Learning about MCP for iOS and macOS development" 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.

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

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

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.

MCP server providing full read/write access to Whoop wearable data, including recovery, sleep, workouts, journal, and more, via Whoop's private iOS API.

Synchronizes an iOS app's most recently synced data to a self-hosted server and exposes it through authenticated, read-only Remote MCP tools for querying that data.

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.

Connects Claude to Strava data for natural language queries about rides, stats, and activities.

Read-only MCP server for accessing glucose readings, charts, logbook, and statistics from LibreLink Up sensors, supporting any MCP client.

Strength-training app Claude can write to: reads real workout history (planned vs actual) and writes planned workouts back into the Tally iOS app. First-party hosted remote MCP server secured with OAuth 2.1 (PKCE + dynamic client registration).

MCP server for the Fitbit Web API with OAuth PKCE, local cache, and trend analysis.

Provides read-only access to Withings health metrics including body composition, sleep, workouts, and ECG data with local SQLite caching and trend analysis. Features incremental synchronization, automatic OAuth token refresh, and supports all 200+ Withings measurement types for comprehensive health tracking.

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 users to describe workouts in plain English and have them created as structured Garmin Connect workouts with pace, HR, power, cadence targets, and repeat blocks. Also provides full workout lifecycle management including listing, updating, deleting, and scheduling to the calendar.

An MCP server that converts structured cycling workout specs into MyWhoosh .zwo and Garmin Connect workout files, with tools for validation, description, and rendering. It also includes skills for uploading workouts to both platforms.

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.

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.

Privacy-first MCP server for querying personal health and finance data with AI. Built with Python, FastMCP, and SQLite. Local-first and open source.

Enables retrieval of InBody body composition data including profile, scan history, and full metrics via MCP tools.