How to Use the Harvard WHO Health MCP in Google ADK

Q: How do I initialize the Harvard WHO Health MCP Server inside a Google ADK agent?

You instantiate the McpToolset class with the server's HTTP endpoint URL. Pass this toolset instance into your LlmAgent configuration to expose the health data tools to your Gemini model.

Q: Does the Google ADK support tool filtering for the Harvard WHO Health tools?

Yes, you can use the toolnames parameter when defining your toolset in Python. This limits your agent's access to specific tools like getlifeexpectancy while hiding others.

Connect WHO epidemiological data directly to your Google ADK agent for long-context Gemini analysis and BigQuery workflows.

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Connect Harvard WHO Health MCP to Google ADK

Create your Vinkius account to connect Harvard WHO Health 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 Harvard WHO Health with Google ADK

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Inject WHO metrics into Google ADK pipelines

You retrieve country-specific health workforce metrics using `get_health_workforce` to map physician and nurse density against local outcomes in Google ADK. The Google ADK framework lets your Gemini agent ingest this workforce data directly, feeding it into your larger enterprise cloud infrastructure. This MCP Server handles the connection over standard HTTP or Stdio transports for your Google ADK agent. Your agent parses the exact counts of dentists, pharmacists, and doctors, combining this live WHO data with your existing datasets stored in BigQuery.

Run long-context disease analysis with Google ADK

You pull historical mortality tables using `get_mortality` and `get_maternal_health` to feed Gemini's million-token context window in your Google ADK pipeline. The Google ADK allows your agent to process decades of maternal and child mortality metrics in a single long-context reasoning loop. You restrict the exposed tools using the `tool_names` filter in your Google ADK Python setup. This ensures your Gemini agent only sees the specific WHO mortality endpoints it needs, preventing it from wasting tokens on unrelated water or sanitation queries.

Query immunization and NCD indicators at scale

You search and retrieve specific global health metrics using `search_indicators` and `get_ncd` to build risk profiles in your Google ADK system. This MCP Server exposes over a thousand indicators that your Google ADK agent can search dynamically during execution. You pass the server parameters directly to the Google ADK `McpToolset` constructor. Your Gemini agent then queries vaccination rates for polio or measles and immediately compares them against chronic disease trends.

Setup guide

Set up Harvard WHO Health 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 Harvard WHO Health 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="Harvard WHO Health_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Harvard WHO Health tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by WHO GHO. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Harvard WHO Health MCP in Google ADK

You instantiate the `McpToolset` class with the server's HTTP endpoint URL. Pass this toolset instance into your `LlmAgent` configuration to expose the health data tools to your Gemini model.

Yes, your agent can fetch health expenditure or immunization data from the server and pass it directly to your BigQuery connector. This allows your pipeline to join global WHO metrics with internal healthcare datasets.

Yes, you can use the `tool_names` parameter when defining your toolset in Python. This limits your agent's access to specific tools like `get_life_expectancy` while hiding others.

The ADK takes advantage of Gemini's large context window to process detailed multi-country tables returned by `compare_countries`. Your agent can analyze ten-year trend lines without running out of memory.

Your queries for global disease statistics and population metrics pass through ephemeral V8 sandboxes. The connection token is verified instantly, and no health indicator data is saved or logged on the external hosting platform.

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