How to Use the Withings MCP in Google ADK

Q: How does the Withings MCP Server handle heart rate monitoring with Google ADK?

You call getheartrate to get specific, point-in-time measurements. You can also use getmeasurements and set the appropriate meastype for a direct check of the user's pulse.

Q: Can I access weight data using Withings and Google ADK?

Yes, you run getmeasurements, specifying 1 as the meastype. The server requires a date string (YYYY-MM-DD) to ensure accurate retrieval of historical records.

Q: What fitness data does Withings provide to Google ADK?

The getworkouts tool pulls everything from running and cycling—distance, calories, duration. Additionally, you can check user goals using getusergoals.

Q: How do I track device changes with Withings and Google ADK?

Use the getuserdevices tool to list every connected item. This is key for your agent's setup, letting you know exactly what hardware data streams are available.

Process health data with Google ADK using the Withings MCP Server.

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Connect Withings MCP to Google ADK

Create your Vinkius account to connect Withings to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Withings with Google ADK

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Retrieve detailed activity and measurements

Your agent can get daily summaries via `get_activity`, or pull specific readings like heart rate from `get_heart_rate`. Use `get_measurements` to grab weight, height, and blood pressure details. It’s a solid way to build longitudinal health records for BigQuery.

Analyze sleep patterns with the MCP Server

The server offers two sleep tools: `get_sleep_summary` for quick daily views, and `get_sleep_details` for stage-by-stage analysis. This lets your agent process high-quality rest data alongside other user metrics.

Build comprehensive fitness pipelines with Google ADK

The system handles both recorded workouts via `get_workouts`, and real-time updates through `subscribe_notifications`. This means your agent can monitor ongoing activity or pull historical training data efficiently.

Setup guide

Set up Withings MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Withings tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Withings_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Withings tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Withings MCP in Google ADK

You call `get_heart_rate` to get specific, point-in-time measurements. You can also use `get_measurements` and set the appropriate `meastype` for a direct check of the user's pulse.

Yes, you run `get_measurements`, specifying 1 as the `meastype`. The server requires a date string (YYYY-MM-DD) to ensure accurate retrieval of historical records.

The `get_workouts` tool pulls everything from running and cycling—distance, calories, duration. Additionally, you can check user goals using `get_user_goals`.

Use the `get_user_devices` tool to list every connected item. This is key for your agent's setup, letting you know exactly what hardware data streams are available.

The server manages physiological measurements like weight, blood pressure (systolic/diastolic), body temperature, and heart rate pulses. This covers most basic health metrics.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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