How do I filter for specific measurements like Body Fat or Blood Pressure?

Use the `meastype` parameter with the `get_measurements` tool. Common types: 1 (Weight), 4 (Height), 8 (Fat Mass), 9 (Diastolic BP), 10 (Systolic BP), 11 (Heart Pulse), 71 (Body Temperature).

What is the difference between sleep summary and sleep details?

`get_sleep_summary` returns one overall score and total duration per night. `get_sleep_details` returns high-frequency intraday data, detailing exactly what time you entered REM, deep sleep, or woke up throughout the night.

Can I receive real-time notifications when I step on the scale?

Yes, use the `subscribe_notifications` tool with an `appli` ID of 1 (Weight). Withings will then send a POST webhook to the callback URL you specify the moment a new weight measurement is synced.

Withings MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Withings
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Withings through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "withings": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Withings, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Withings MCP Server

Connect your Withings account to any AI agent to unlock deep insights into your health, wellness, and fitness data collected by Withings smart scales, watches, and medical devices.

LangChain's ecosystem of 500+ components combines seamlessly with Withings through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Medical Measurements — Track weight, body fat %, systolic/diastolic blood pressure, and heart pulse trends over time
Sleep Analytics — Access daily sleep scores, deep/light/REM sleep stage durations, and sleep efficiency metrics
Activity Tracking — Analyze daily step counts, active calories burned, and precise intraday activity levels
Workout Logging — Review distinct workout sessions (running, swimming, cycling) with categorizations and duration
Device Management — Check the battery status and connection status of your Withings hardware fleet
Real-time Notifications — Configure webhooks to receive instant alerts when new measurements (like a morning weigh-in) are recorded

The Withings MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Withings to LangChain via MCP

Follow these steps to integrate the Withings MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Withings via MCP

Why Use LangChain with the Withings MCP Server

LangChain provides unique advantages when paired with Withings through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Withings MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Withings queries for multi-turn workflows

Withings + LangChain Use Cases

Practical scenarios where LangChain combined with the Withings MCP Server delivers measurable value.

RAG with live data: combine Withings tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Withings, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Withings tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Withings tool call, measure latency, and optimize your agent's performance

Withings MCP Tools for LangChain (10)

These 10 tools become available when you connect Withings to LangChain via MCP:

get_activity

Get daily activity summaries (steps, calories)

get_heart_rate

Get specific heart rate measurements

get_intraday_activity

Get high-frequency intraday activity data

get_measurements

Use meastype to filter (1=Weight, 4=Height, 9=Diastolic BP, 10=Systolic BP, 11=Heart Pulse, 71=Body Temp). Dates should be YYYY-MM-DD. Get physiological measurements (weight, blood pressure, etc)

get_sleep_details

Get detailed sleep data (stages and states)

get_sleep_summary

Get daily sleep summaries

get_user_devices

List user's Withings devices

get_user_goals

Get user health and fitness goals

get_workouts

g., running, swimming, cycling) with their specific duration, calorie burn, distance, and activity category. Get recorded workouts and exercises

subscribe_notifications

g. immediately after a user steps on a scale). Appli codes: 1(weight), 4(BP), 16(activity), 44(sleep). Subscribe to Withings webhook notifications

Example Prompts for Withings in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Withings immediately.

"Retrieve my weight and body fat measurements for the last 30 days."

"What was my sleep score and total sleep time last night?"

"Analyze my activity levels over the weekend. Did I hit my step goals?"

Troubleshooting Withings MCP Server with LangChain

Common issues when connecting Withings to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Withings + LangChain FAQ

Common questions about integrating Withings MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.