"How to implement Active Directory authentication in a project" matching MCP servers:

Hosted MCP server that syncs health data from Apple Health, Fitbit, Oura, and Google Health Connect, enabling Claude and ChatGPT to query workouts, sleep, nutrition, and recovery in plain English with interactive charts.

Exposes Garmin Connect health and activity data (steps, sleep, heart rate, etc.) via MCP tools, with built-in login and MFA support.

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 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.

Enables AI assistants to read your SisRUN training plan with your own credentials and answer questions about prescribed workouts, like weekly coach plans, in a structured format.

A local MCP server that caches Garmin Connect data in SQLite for fast, read-only queries, with tools for bulk import, rate-limited sync, and failure alerts.

Enables AI assistants to access and modify a user's real GymTimer workout and nutrition data stored in private iCloud, allowing natural-language queries about training history and the creation of workout templates and meal plans.

Enables Claude to manage MyFitnessPal food diaries, nutrition goals, exercises, body measurements, and water intake via a remote MCP server using session cookie authentication.

Enables access to Withings Health API data including body measurements, activity tracking, sleep analysis, workouts, and heart rate monitoring through OAuth2 authentication.

Exposes WHOOP recovery, sleep, strain, and workout metrics to MCP-compatible AI assistants using OAuth 2.0 authentication, enabling daily wellbeing snapshots, trend analysis, and workload recommendations.

Enables access to WHOOP fitness and health data through all WHOOP v2 API endpoints. Supports OAuth 2.0 authentication and provides comprehensive access to user profiles, physiological cycles, recovery metrics, sleep analysis, and workout data.

An MCP server for interacting with the Wahoo Cloud API to manage workouts, routes, training plans, and power zones. It enables users to list, retrieve, and create fitness data through secure OAuth 2.0 authentication.

Integrates with Whoop API v2 to access user profile, sleep, recovery, cycles, and workout data via natural language, with OAuth2 authentication and automatic token refresh.

Enables searching FatSecret's food and recipe database, and managing personal food diary, weight, exercise, saved meals, and favorites, with multi-user support and secure OAuth authentication.

A Model Context Protocol server that provides language models with access to Strava API data, allowing them to query and analyze athlete activities from Strava.

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.

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.

Connects Aidlab wellness data to AI tools through MCP, providing read-only access to daily summaries, steps, heart rate, HRV, sleep, activities, and profile with OAuth authentication.

This MCP server exposes read-only Apple Health data to AI assistants via three tools (health_now, health_detail, health_trends), deployable to Cloudflare with a one-click button and no coding required.

This MCP server enables logging workouts in plain language through AI assistants and provides tracking of sessions, programs, records, estimated 1RM, and per-muscle load, with coaching informed by the user's logged data.