"API Access for Pokémon-related Data" matching MCP servers:

MCP server for Cronometer nutrition tracking using the mobile API. Enables food logging, nutrition data retrieval, diary management, and fasting tracking.

Enables retrieval of InBody body composition data including profile, scan history, and full metrics via MCP tools.

MCP server for Cronometer nutrition tracking, enabling food diary management, nutrition data retrieval, food search, and biometric tracking via Cronometer's mobile REST API.

Provides local MCP tools to query your own Xiaomi Mi Fitness health data (sleep, workouts, heart rate, etc.) stored in a local SQLite database, enabling AI assistants to access personal health records without exposing credentials.

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.

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.

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 users to search and retrieve fitness exercise information from the Api Ninjas database. It supports filtering by exercise name, target muscle, type, and difficulty level.

MCP server for the Fitbit Web API with OAuth PKCE, local cache, and trend analysis.

Provides read-only access to Withings health metrics including body composition, sleep, workouts, and ECG data with local SQLite caching and trend analysis. Features incremental synchronization, automatic OAuth token refresh, and supports all 200+ Withings measurement types for comprehensive health tracking.

MCP server for the Google Health API: heart rate, activity, sleep, SpO2, HRV, ECG and irregular-rhythm notifications, read into a local SQLite cache for fast offline queries and trend analysis. OAuth 2.0 with automatic token refresh, incremental sync, a cache-only offline mode, and a doctor command that diagnoses a setup without spending quota.

Enables AI assistants to read Technogym mywellness training history, including workout sessions, per-exercise set data, per-second exercise analytics, and heart-rate traces.

Provides read-only access to Oura ring biometrics via the Oura API, enabling Claude to query daily summaries, sleep, readiness, stress, workouts, baselines, and heart rate data. Designed to complement a Strava connector for joint analysis of training and recovery.

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.

Provides Claude with real-time access to local health data including sleep, recovery, strain, and workouts from WHOOP and Apple Health, enabling informed context-aware interactions.

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.

Connects WHOOP fitness tracker data to AI assistants like Claude and ChatGPT, enabling natural language queries about recovery, sleep, strain, and trends.

A stateless MCP server that normalizes strength training logs into a deterministic canonical schema, enabling consumers to build analytics downstream without storing data server-side.