How to Use the WHO GHO MCP in CrewAI

Q: How do I structure an investigation using WHO GHO and CrewAI?

Give your crew three roles: 1) Researcher (uses searchwhoindicators), 2) Reporter (uses getwhocountryprofile), and 3) Analyst (uses getwhoindicatordata). The workflow is sequential, passing memory between the agents.

Run autonomous research operations on global health with WHO GHO using CrewAI's specialized agents.

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Connect WHO GHO MCP to CrewAI

Create your Vinkius account to connect WHO GHO to CrewAI 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 WHO GHO with CrewAI

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Researching Health Indicators

Designate one agent (the Researcher) to use `search_who_indicators`. This specialization finds the correct codes for all 2,200+ global health indicators. The output of this tool becomes shared memory for the rest of your crew. The Moderator Agent can then review these found codes before passing them off to the Analyst agent.

Profiling a Country's Status

Assign an agent the role of Reporter. This specialized agent runs `get_who_country_profile` against specific ISO-3 country codes. It summarizes the findings, providing immediate context for the rest of the crew. The Reporter doesn't just pass raw data; it presents a clear summary that the team can act on.

Analyzing Historical Metrics

The Analyst agent handles `get_who_indicator_data`. It takes the codes found earlier and pulls deep, multi-year metrics, including sex disaggregation. This is crucial for comparative analysis. The crew's collaboration means one agent finds the data, another formats it, and a third generates the final report.

Setup guide

Set up WHO GHO MCP in CrewAI

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke WHO GHO tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="WHO GHO Analyst",
    goal="Access and analyze WHO GHO data via MCP.",
    backstory="Expert analyst with direct WHO GHO access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent WHO GHO transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

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

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="WHO GHO Analyst",
        goal="Access and analyze WHO GHO data via MCP.",
        backstory="Expert analyst with direct WHO GHO access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent WHO GHO transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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. 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 WHO GHO MCP in CrewAI

Give your crew three roles: 1) Researcher (uses `search_who_indicators`), 2) Reporter (uses `get_who_country_profile`), and 3) Analyst (uses `get_who_indicator_data`). The workflow is sequential, passing memory between the agents.

Yes. You can set up a multi-agent process where one agent locates codes using `search_who_indicators` and another uses those codes to execute `get_who_indicator_data`, ensuring the full cycle is covered.

The Reporter agent can handle a list of ISO-3 countries. The crew runs `get_who_country_profile` for each one, compiling all the individual snapshots into one cohesive final report.

The server accesses public health metrics and demographic information from the World Health Organization. The resulting data types include life expectancy, disease prevalence rates, and coverage statistics.

This MCP Server only handles publicly available health metrics and demographic data sourced from the World Health Organization. It never touches private individual records.

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