The Pierre Fitness API is a multi-protocol fitness data API that supports securely obtaining fitness data from providers such as Strava and Fitbit. It provides intelligent analysis for AI applications through MCP, A2A, and REST APIs, including enterprise-level API management, real-time analysis, and intelligent analysis of multiple sports types.

A TypeScript server that connects Hevy fitness data with language models and provides tools for fitness history, training progress, and personal records through the MCP protocol.

An MCP server that connects to Garmin Connect to obtain and display users' fitness and health data

Personal health tracking MCP server, integrated with AI analysis function, supporting fitness, nutrition, and journal management

An MCP server implemented for the Hevy fitness app API, providing fitness data management functions

Fitbit MCP is an unofficial implementation of the Model Context Protocol that allows AI assistants to access and analyze users' Fitbit health and fitness data through the Fitbit public API.

This is an MCP server project that implements the WHOOP API, providing functions to interact with WHOOP fitness data, including access to user profiles, sleep, workouts, recovery, and cycle data.

The Health & Fitness Coach MCP is a comprehensive project that combines AI intelligence with traditional fitness applications. It enables intelligent interaction between AI tools and fitness data through the Model Context Protocol (MCP) and consists of two major components: a web application and an MCP server.

The Health & Fitness Coach MCP is an AI - driven comprehensive fitness tracking application, including a Web dashboard and an MCP server. It enables intelligent interaction between the AI assistant and fitness data through the Model Context Protocol, providing functions such as exercise recording, nutrition tracking, and personalized plan generation.

Implementation of the MCP server for the Hevy API, providing a toolset for interacting with the Hevy fitness platform, including functions such as training record and routine management.

This is an MCP server project based on the OpenAPI specification, used for the Google Fitness API, supporting automatic generation and multiple transport modes.