# Withings MCP MCP

> Withings MCP connects any AI agent to health data from Withings devices. It lets you pull longitudinal records covering weight trends, blood pressure readings, detailed sleep cycles, step counts, heart rate metrics, and workout logs over time. This is for deep analysis of personal biometric patterns.

## Overview
- **Category:** iot-hardware
- **Price:** Free
- **Tags:** connected-health, biometric-tracking, sleep-analytics, cardiovascular-health, health-data, wearable-integration

## Description

This connection gives your agent access to everything recorded by Withings smart scales and watches—from daily activity summaries to specific medical measurements like systolic and diastolic blood pressure. You can query detailed sleep scores, analyze how many steps you took intraday, or review full workout logs for swimming, running, and cycling.

The real value shows up when your agent chains these data streams together. For instance, correlating a week's worth of high-intensity workouts with subsequent deep sleep stages creates immediate insight that manual dashboard viewing misses. Because the process runs on Vinkius, you get full visibility into every tool call, seeing exactly which measurements influenced the final analysis—nothing happens in the dark. This capability lets you build complex automations spanning multiple data types using one agent connection.

## Tools

### get_activity
Pulls daily summaries of steps taken and calories burned.

### get_heart_rate
Retrieves specific heart rate measurements for a given date range.

### get_intraday_activity
Gets high-frequency activity data points throughout the day, useful for detailed movement analysis.

### get_measurements
Fetches key physiological measurements like weight, body temperature, and blood pressure using specific codes (e.g., 1=Weight).

### get_sleep_details
Provides a deep dive into sleep data, including the exact duration of REM, light, and deep sleep stages.

### get_sleep_summary
Retrieves a simplified view of daily sleep metrics, like total hours slept and overall score.

### get_user_devices
Lists all Withings hardware devices associated with the user's account.

### get_user_goals
Retrieves pre-set health and fitness goals established by the user.

### get_workouts
Pulls records of completed exercise sessions, including distance, duration, and category (running, swimming, cycling).

### subscribe_notifications
Sets up webhooks to receive instant alerts when critical measurements are logged by the user.

## 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 weight and body composition trends
The agent retrieves historical readings for weight, body fat percentage, and other core metrics.

### Detail sleep stages and scores
You can get detailed breakdowns of your sleep, including time spent in deep, light, and REM stages.

### Track high-frequency daily activity
The agent pulls granular data on movement throughout the day, going beyond simple step counts.

### Get specific vital signs history
You can retrieve historical measurements for heart rate and blood pressure readings.

### Review recorded exercise sessions
The agent pulls records of completed workouts, including distance, duration, and calories burned.

### Receive real-time health alerts
You can set up webhooks so the system sends instant notifications when new readings occur (like a morning weigh-in).

## Use Cases

### A runner needs to know if their long-distance training affects sleep.
The agent combines data from the `get_workouts` tool (for running distance) with the `get_sleep_details` tool. The resulting analysis pinpoints a consistent drop in deep sleep stages following workouts over 15 miles.

### A coach needs to check if weight loss is stalled.
The agent runs comparisons using `get_measurements` (weight and body fat) against the user's established target goals from `get_user_goals`, immediately flagging a stagnation trend that requires intervention.

### A developer needs to build an automated daily health report.
The agent is configured via `subscribe_notifications` to trigger on morning weigh-ins. This instantly feeds the new reading into a larger system for historical charting, eliminating manual data entry.

### A researcher needs longitudinal biometric analysis.
By calling `get_measurements` for systolic/diastolic BP and combining it with heart rate from `get_heart_rate`, the agent builds a multi-month dataset to track cardiovascular health trends.

## Benefits

- See trends over time. Instead of just looking at today's weight, you can use `get_measurements` to track body fat percentage changes across months, giving a clear picture of progress.
- Connect cause and effect. You can correlate the activity level reported by `get_workouts` with sleep quality details from `get_sleep_details`, identifying if intense exercise impacts deep REM cycles.
- Stay in the loop automatically. By setting up notifications via `subscribe_notifications`, your agent gets an instant alert when a critical metric, like blood pressure, changes significantly.
- Analyze movement intensity. Don't just check steps using `get_activity`. Use `get_intraday_activity` to analyze patterns of high-frequency movement throughout the day for deeper insights.
- Build comprehensive client views. By chaining together data from `get_user_goals`, `get_workouts`, and `get_activities`, you get a single view showing compliance relative to set targets.

## How It Works

The bottom line is you get a single connection point into decades of personal health records that your AI client can query using structured calls.

1. Subscribe to this MCP, then register an app at the Withings Developer Portal to get your OAuth Access Token.
2. Provide that access token to your AI client; it connects the agent directly to the physiological data stream.
3. Your agent queries the relevant tools—for example, asking for sleep summaries and comparing them against workout logs.

## Frequently Asked Questions

**How do I check my weight and body fat trends using the Withings MCP?**
You use `get_measurements`. This tool lets you query historical data for multiple metrics, so your agent can show a trend line of both weight and body fat percentage over time.

**Can I get my workout history with the Withings MCP?**
Yes. Call `get_workouts`. This tool pulls all recorded exercise sessions, giving you distance, duration, and category for running, swimming, or cycling.

**Does the Withings MCP handle real-time alerts?**
It does. Use `subscribe_notifications` to set up webhooks. This means when a new reading occurs on your device, the system sends an instant alert that your agent can process.

**Which tool do I use for general daily movement data?**
The best tools are `get_activity` and `get_intraday_activity`. Use the former for a simple total, but use the latter if you need high-frequency details on how your movement spread throughout the day.

**How does using `get_sleep_details` give me insights into my sleep stages?**
It returns a deep breakdown of your night's rest. You get specific data points for light, deep, and REM phases, which gives context beyond just the daily sleep score.

**What information does `get_user_devices` provide about my Withings hardware?**
It lists every connected Withings device tied to your account. You'll see the model and connection status for all hardware, allowing you to audit your entire setup.

**If I use `get_measurements`, how do I track my blood pressure trends?**
It provides separate data points for both systolic and diastolic values. This structured output lets your agent compare these key metrics over time to spot patterns.

**How can I check the goals I'm working toward using `get_user_goals`?**
It fetches your current health objectives set in the Withings app. Your agent can then compare real-time metrics against these stated targets for compliance analysis.