"A tool for finding people on LinkedIn based on their area of focus" matching MCP servers:

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

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.

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.

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.

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.

An MCP server that provides access to detailed exercise-to-muscle mapping data for over 320 exercises and 65 muscles. It enables users to analyze workout coverage, find exercise alternatives based on muscle overlap, and search for specific exercise activation data.

Local-first MCP server that reads Apple Health export files (export.xml/zip) and exposes activity, sleep, HRV, and workout data to AI agents, keeping all data on your machine.

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 stateless MCP server that exposes tools for evidence-based strength training, including classical powerlifting programs and fatigue management.

MCP server for the Hevy fitness tracking app, enabling management of workouts, routines, exercise templates, folders, and webhooks through AI assistants.

Read your Samsung Health CSV/ZIP exports — activity, sleep, heart, stress — locally. It is a local-first MCP server that keeps your tokens on your machine.

Enables Claude Desktop to access and analyze Garmin wearable health data including sleep, HRV, Body Battery, and activity metrics. Users can query their health trends, track recovery, and generate interactive HTML dashboards using natural language.

Trainzilla MCP connects Claude to your Trainzilla coach account, turning your client roster, programming, and habit tracking into something you can manage conversationally. Built for fitness coaches running their practice on Trainzilla, it lets Claude pull up client profiles and metrics, build and review workout and diet plans, create and assign habits, run quick calculations (TDEE, macros, 1RM),

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.

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.

A local, read-only Model Context Protocol server for an athlete's Strava profile and activities, enabling retrieval of profile data, activity lists (with paging and date filters), and detailed activity information via standard input/output for MCP hosts.

Turns any AI assistant into a physiological AI running coach by abstracting fitness APIs and exposing 70+ structured analytical MCP tools based on endurance models.

Enables users to interact with their Strava data through natural language to analyze workouts, track fitness progress, and explore routes. It supports retrieving detailed activity stats, heart rate data, and segment insights directly within AI assistants.