# Withings MCP > Withings MCP connects your AI agent directly to health and fitness data from Withings devices, including smart scales, watches, and medical monitors. Pull detailed records on weight trends, body fat percentage, blood pressure (systolic/diastolic), heart rate variability, sleep cycles, and workout logs. You can also set up instant webhooks for alerts when new readings are recorded. ## Overview - **Category:** iot-hardware - **Price:** Free - **Tags:** connected-health, biometric-tracking, sleep-analytics, cardiovascular-health, health-data, wearable-integration ## Description Need to understand what your biometric data actually means? This MCP lets you connect your AI client to Withings hardware, giving you deep insights into your health journey. Instead of manually logging numbers from multiple sources, your agent pulls everything together—sleep scores, daily steps, and blood pressure readings—and presents clear trends over time. You can ask complex questions like, 'How did my sleep quality change when I started cycling?' The system handles the data retrieval, letting you focus on what to do next. Because this MCP is hosted on Vinkius, you connect once from any compatible client and get access to all your health tracking tools in one place. ## Tools ### get_activity Pulls a daily summary of steps and total calories burned. ### get_heart_rate Retrieves specific heart rate measurements taken at certain times. ### get_intraday_activity Gathers detailed, high-frequency activity readings throughout a day. ### get_measurements Collects key physiological data points like weight, body temperature, and blood pressure for specific dates. ### get_sleep_details Provides a granular breakdown of sleep stages (deep, light, REM) over the night. ### get_sleep_summary Generates an overall summary and score for the previous night's rest. ### get_user_devices Lists all Withings hardware devices linked to your account. ### get_user_goals Retrieves the health and fitness goals you have set for yourself or a client. ### get_workouts Gets detailed records of completed exercises, including type, distance, and duration. ### subscribe_notifications Sets up automated alerts for new data entries like weigh-ins or activity spikes. ## Prompt Examples **Prompt:** ``` Retrieve my weight and body fat measurements for the last 30 days. ``` **Response:** ``` I've retrieved your measurements. Your weight started at 82.5kg 30 days ago and is currently 81.2kg. Your body fat mass trended down from 19.4% to 18.8%. ``` **Prompt:** ``` What was my sleep score and total sleep time last night? ``` **Response:** ``` Last night you slept for a total of 7 hours and 12 minutes, achieving a Sleep Score of 88 (Good). You fell asleep in just 8 minutes but woke up 3 times during the night. ``` **Prompt:** ``` Analyze my activity levels over the weekend. Did I hit my step goals? ``` **Response:** ``` Looking at your activity data: On Saturday you took 12,450 steps and burned 2,400 calories (Goal met!). On Sunday, you took 6,200 steps and logged a 45-minute Cycling workout burning 450 calories, keeping your activity high despite lower steps. ``` ## Capabilities ### Analyze Vital Sign Trends Check how metrics like weight, blood pressure, or body fat change over weeks or months. ### Assess Sleep Quality Get a breakdown of your sleep stages (deep, light, REM) and overall daily sleep scores. ### Track Activity Metrics Analyze cumulative step counts, active calories burned, and high-frequency movement patterns throughout the day. ### Review Exercise Logs Pull comprehensive details on specific recorded workouts, including distance, duration, and calorie expenditure for running or swimming sessions. ### Set Up Instant Alerts Configure the system to send immediate notifications whenever a new measurement (like a morning weigh-in) is completed. ## Use Cases ### Investigating a Stressful Week A user asks their agent to analyze data from the past seven days. The agent uses `get_sleep_summary` and cross-references it with heart rate measurements using `get_heart_rate`. It finds that every night they had over 6 hours of work, their sleep score dropped by an average of ten points. ### Client Compliance Check A personal trainer needs to see if a client is meeting goal parameters. The agent uses `get_user_goals` and compares that data against the activity logs retrieved using `get_workouts`, flagging any time the client missed their weekly cycling target. ### Long-term Health Monitoring A researcher tracks participants over a year. They programmatically pull weight and blood pressure readings via `get_measurements` to build statistical models, identifying subtle trends that would be impossible to spot by hand. ### Pre-Workout Readiness Check Before a big race, an athlete asks the agent for their current status. The MCP quickly checks `get_sleep_details` and compares it against recent activity levels (`get_activity`) to give them a readiness score. ## Benefits - Correlate different metrics easily. Instead of checking a spreadsheet to see if weight changes match sleep quality dips, you can ask the agent directly for the relationship between `get_measurements` and `get_sleep_details`. - Avoid missing data points. By setting up webhooks using `subscribe_notifications`, you get instant alerts when critical readings occur—like a high blood pressure spike or a morning weigh-in. - Analyze movement patterns beyond just steps. The `get_intraday_activity` tool lets you see precise, moment-by-moment activity data that simple step counts miss. - Get full context on your fitness routine. You can pull detailed workout logs using `get_workouts`, which gives more than just a type; it provides distance and duration for running, swimming, or cycling. - Keep track of everything in one place. The MCP centralizes access to weight (via `get_measurements`), activity summaries (`get_activity`), and sleep metrics, eliminating the need for multiple logins. ## How It Works The bottom line is, you give your agent permission via a token, and it starts pulling raw health numbers directly from Withings into conversation. 1. Subscribe to this MCP on Vinkius. 2. Go to the Withings Developer Portal and generate an OAuth Access Token for your application. 3. Use your AI client to query specific data points, like querying weight trends or sleep details. ## Frequently Asked Questions **How often can I use the Withings MCP to get_measurements?** You can query this tool frequently. It's designed for continuous data analysis, allowing you to pull historical readings of weight and blood pressure whenever your project requires it. **Does the Withings MCP help me track my body fat percentage?** Yes, `get_measurements` handles body composition tracking. You can request history for both weight and body fat percent over a specified time range. **Can I use get_workouts to compare different exercise types?** Absolutely. This tool pulls full details on specific workouts, allowing you to compare the distance and calorie burn between cycling sessions versus running sessions in one place. **What if I want notifications for when my weight changes? Does subscribe_notifications handle that?** Yes. By using `subscribe_notifications` with the appropriate code, you can configure instant alerts to fire whenever a new weigh-in measurement is recorded on your device. **Is get_sleep_summary better than get_sleep_details?** They serve different purposes. Use `get_sleep_summary` for the quick, overall score and total time. Use `get_sleep_details` when you need to analyze the specific duration of REM versus deep sleep stages.