"An e-commerce platform for building online stores" matching MCP servers:

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

Connects AI assistants to fitness data from over 150 wearables including Strava, Garmin, and Fitbit through the Model Context Protocol. It provides 47 tools for sports science-based analysis, training load management, recovery tracking, and personalized nutrition planning.

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.

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.

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.

An MCP server that lets Claude plan cycling training in intervals.icu, upload workouts to the calendar, and review planned versus actual outcomes, fitness trends, and power curves.

Query Apple Health export data with an LLM via a semantic layer that avoids common data traps, enabling accurate natural-language queries about health metrics. Optionally imports CPAP therapy data for correlation.

Exposes the Oura API v2 as an MCP server with tools to query all 19 data collections (e.g., sleep, heartrate) with automatic pagination and explicit truncation warnings.

Provides read-only access to your Garmin Connect health data, including sleep, HRV, body battery, stress, training readiness, and activities, through an MCP server.

Query your Apple Health data including sleep, heart rate, steps, workouts, and more by ingesting an exported XML archive into a local SQLite database.

An MCP server that transforms Garmin data into compact, verdict-first coaching reports for LLMs, computing metrics like CTL/ATL/TSB and ACWR to answer training readiness questions.

Enables an LLM to search a movement library, log single-movement and multi-movement workout results, and pull complete logged training history plus PR trends for Beyond the Whiteboard straight from a chat. All logged entries are posted privately, and session authentication can refresh automatically.

MCP server to read daily activity, sleep, heart rate, and body metrics from Google Health API, allowing AI assistants like Claude to access your health data. Optionally syncs health metrics to an Obsidian vault.

Enables read-only access to RENPHO Health smart scale measurements through MCP, allowing users to retrieve latest readings, body composition history, and weight trends via an MCP client.

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

An MCP server that exposes the Hevy fitness API as 22 tools, enabling AI agents to manage workouts, routines, exercise templates, and body measurements through natural language.

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.

Minimalist Strava integration for Claude with 7 focused tools for querying athlete stats, activities, zones, and segment analysis.

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.