"FOX" matching MCP servers:

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 and other MCP apps to query the user's own activity and health data—sleep, HRV, Body Battery, stress, heart rate, steps, and workouts—locally and read-only.

Provides local, Keychain-secured access to all 26 Garmin Connect Personal API GET endpoints plus 8 summary tools. Enables users to query sleep, HRV, Body Battery, activities, profile, weight, and other connected health data through their own Personal API key.

Enables Claude to read a user's Oura Ring data—including sleep, readiness, activity, stress, workouts, heart rate, and personal info—through a self-hosted, read-only connector deployed to the user's own Vercel account.

Gives Claude read-only access to your own ring's health data — sleep, readiness, HRV, heart rate, activity, workouts, stress, resilience, SpO2, VO2 max and cardiovascular age — from claude.ai, desktop, and mobile. Runs as a private remote server on your own Cloudflare Worker, locked to a single account with OAuth-encrypted tokens and no stored health 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.

Enables AI apps to query a user's Google Health data—such as sleep, heart rate, HRV, activity, and paired devices—through read-only tools deployed privately in the user's own Firebase project.

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

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.