"Attribution and Contribution Analysis in Data Science and Economics" 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.

MCP server for tracking nutrition meals and workouts, integrating with claude.ai to manage food logs, macros, exercise catalogs, and generate daily/weekly summaries.

Serves read-only archived ResMed CPAP data from a local SQLite database, enabling MCP clients to query nightly summaries, raw signals, and sync status over the LAN.

A Model Context Protocol server that enables Claude to search and access detailed nutritional information from the USDA's FoodData Central database.

MyChart MCP Server

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.

MCP server for analyzing running data from Intervals.icu, offering tools for athlete profiles, activity details, fitness trends, and running summaries.

Enables querying of current A\&E waiting times, specialist outpatient waiting times, and general outpatient clinic quotas in Hong Kong using natural language through MCP.

MCP server that provides access to Hong Kong government city data, including ambulance service indicators, via a FastMCP interface.

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.

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 users to describe workouts in plain English and have them created as structured Garmin Connect workouts with pace, HR, power, cadence targets, and repeat blocks. Also provides full workout lifecycle management including listing, updating, deleting, and scheduling to the calendar.

MCP server that reads glucose data from a FreeStyle sensor via the LibreLinkUp API, providing current glucose and history with explicit coverage and gaps.

MCP server that lets you ask questions about your Garmin training history in plain language. It ingests FIT files into DuckDB locally and exposes typed tools for analyzing activities, streams, and summaries.

Ask your Oura Ring about sleep, readiness, activity, stress and heart rate in ChatGPT or Claude, in any language. Read-only, 10 task-oriented tools; runs in a sandbox demo mode with no credentials.

Enables Claude Desktop to query and analyze diabetes data from Omnipod 5 and Glooko through natural language, providing clinical audit and triage insights such as time in range, trends, and bolus analysis.

Privacy-first MCP server for querying personal health and finance data with AI. Built with Python, FastMCP, and SQLite. Local-first and open source.

SuperGlookoQuery is a Claude Desktop extension (MCPB) that connects to Glooko diabetes device data and exposes it as clinical analysis tools (time in range, GMI, trends, enriched bolus/basal analysis, charting), for any pump/CGM combination Glooko supports rather than one fixed device. It's a fork of Richard Hall's podquery-mcp, reworked to discover each account's own data shape rather than assumi