"Open Source MCP Server for Managing and Updating MCP Configurations in VSCode" 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.

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.

Enables AI agents to search foods, get nutritional breakdowns, and estimate exercise calories using the Nutritionix API through natural language input.

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 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.

Enables analysis and retrieval of JEFit workout data through natural language. Provides access to workout dates, detailed exercise information, and batch workout analysis for fitness tracking and progress monitoring.

Enables seamless interaction with MyWhoosh API for managing workouts, training sessions, and settings via natural language.

Enables retrieval and analysis of MyFitnessPal nutrition data including daily summaries, meal breakdowns, exercise tracking, and macro/micronutrient analysis. Uses browser cookie authentication to access your personal MyFitnessPal account data through natural language queries.

Model Context Protocol (MCP) server that allows AI assistants to access and analyze your OpenStride training data.

An MCP server specialized in managing and querying gym exercises through a centralized database. It enables users to search for workouts by name or muscle group and retrieve detailed information including sets, repetitions, and rest intervals.

Enables personal trainers to query and summarize client management data—active clients, workouts, physical assessments, retention, check-ins, feedback, and finances—through MCP-compatible AI clients in read-only mode.

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

Official MCP server for exerciseapi.dev — give your AI coding agent direct access to 2,198+ vetted exercises across 12 categories.

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 exposes Whoop API v2 data as tools, enabling natural language queries for cycles, recovery, sleep, workouts, and profile.

Enables AI assistants to interact with the Hevy fitness tracking API for logging workouts, managing routines, and tracking fitness progress.

An MCP server that provides an interface to Google's Fitness API, enabling interaction with fitness data through natural language using the Multi-Agent Conversation Protocol.

MCP server that wraps wger fitness/nutrition management platform, providing 15 tools for exercise search, ingredient nutrition lookup, weight tracking, and more, accessible to any MCP-compatible AI agent.

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