How to Use the Harvard WHO Health MCP in AutoGen

Q: How do I connect Harvard WHO Health to AutoGen?

Install autogen-extmcp. Use mcpservertools with StreamableHttpServerParams to fetch the tools, then pass them into your AssistantAgent constructor.

Q: Does Harvard WHO Health handle schema conversion for AutoGen?

It happens automatically. The McpToolAdapter translates the MCP Server tool definitions into the format your agents expect. You don't have to write custom parsers for the WHO API.

Q: Is maternal mortality data secure during agent conversations?

Yes. When an agent queries getmaternalhealth, the operation runs inside an isolated container. Vinkius handles the endpoint token, and the system retains zero memory of the specific countries or years your agents discussed.

Let AutoGen agents debate global health policy using live WHO statistics.

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Connect Harvard WHO Health MCP to AutoGen

Create your Vinkius account to connect Harvard WHO Health to AutoGen 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 AutoGen

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Fuel AutoGen Debates with WHO Data

The `compare_countries` tool provides the factual baseline for your AutoGen agents to argue over regional health outcomes. One agent pulls a decade of data for three countries, and another agent critiques the underlying trends. You build systems where decisions require deliberation. A policy agent might advocate for more funding based on `get_malaria` incidence, while a financial agent counters by pulling `get_health_expenditure` data to show budget constraints. They negotiate using actual metrics.

Autonomous Health Metric Discovery

The `search_indicators` tool allows your research agents to find relevant WHO codes without your input. If the conversation shifts to cardiovascular health, an agent searches the database, finds the code, and shares it with the group. The next agent in the sequence takes that code and runs `get_indicator_data`. The MCP Server schema converts automatically via `McpToolAdapter`, so your agents never trip over formatting errors when passing parameters back and forth.

Cross-Examine MCP Server Statistics

The `get_health_workforce` tool returns density data for physicians and nurses. Your agents can cross-reference this against `get_life_expectancy` to debate whether healthcare staffing levels directly impact longevity in specific regions. The agents do the heavy lifting. One pulls `get_water_sanitation` stats, another pulls `get_tuberculosis` rates. They discuss the correlation, challenge each other's assumptions, and present you with a synthesized, consensus-driven conclusion.

Setup guide

Set up Harvard WHO Health MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Harvard WHO Health tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Harvard WHO Health_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Harvard WHO Health data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Harvard WHO Health_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Harvard WHO Health data")
    print(result.messages[-1].content)

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 AutoGen

Install `autogen-ext[mcp]`. Use `mcp_server_tools` with `StreamableHttpServerParams` to fetch the tools, then pass them into your `AssistantAgent` constructor.

Yes. The tools are available to any agent you configure. You can have a data-gathering agent pulling WHO stats while an analyst agent reviews the incoming JSON.

It happens automatically. The `McpToolAdapter` translates the MCP Server tool definitions into the format your agents expect. You don't have to write custom parsers for the WHO API.

The server supports both stdio and Streamable HTTP transports. For cloud deployments, the HTTP transport is usually the better choice.

Yes. When an agent queries `get_maternal_health`, the operation runs inside an isolated container. Vinkius handles the endpoint token, and the system retains zero memory of the specific countries or years your agents discussed.

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