How to Use the WHO GHO MCP in LlamaIndex

Q: Can I search historical health data using WHO GHO with LlamaIndex?

Yes. By indexing the results from getwhoindicatordata, you can query past years' performance metrics or configurations against your existing documentation.

Q: Do I need to call multiple tools for WHO GHO with LlamaIndex?

Yes. You typically use searchwhoindicators first to find the codes, then run getwhoindicatordata, and finally pass those results into your indexer.

WHO GHO MCP Server: Index global health data for LlamaIndex RAG applications.

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Connect WHO GHO MCP to LlamaIndex

Create your Vinkius account to connect WHO GHO to LlamaIndex 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 LlamaIndex

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Build Knowledge Bases from WHO Indicators

Use `search_who_indicators` to pull codes for 2,200+ indicators. Once you fetch the results with `get_who_indicator_data`, you index that output directly into a vector store. LlamaIndex turns this live API data into searchable knowledge. You can query past sessions or configurations and get answers grounded in actual health indicator data, not hallucinations.

Get Country Profiles for Context Indexing

`get_who_country_profile` provides a foundational health snapshot using ISO-3 codes. This output is perfect to include as metadata or source chunks when building your unified index. When you run this function, the resulting text becomes part of your knowledge base. You can then search across multiple countries' profiles simultaneously.

Retrieve Specific Metrics with `get_who_indicator_data`

`get_who_indicator_data` returns deep metrics for a chosen indicator, broken down by year and sex. This highly structured data is ideal for indexing. Instead of just showing the numbers, LlamaIndex allows you to query the *meaning* behind these metrics across your entire knowledge index.

Setup guide

Set up WHO GHO MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all WHO GHO MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to WHO GHO tools.",
)
response = await agent.run("List recent WHO GHO data")

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Common questions about WHO GHO MCP in LlamaIndex

The MCP Server output becomes part of a searchable knowledge base. You build RAG applications where live API data and documents combine into one unified, queryable index.

Yes. By indexing the results from `get_who_indicator_data`, you can query past years' performance metrics or configurations against your existing documentation.

The server handles global health indicator data. It sources information on disease prevalence, mortality rates, and life expectancy from 194 countries.

Yes. You typically use `search_who_indicators` first to find the codes, then run `get_who_indicator_data`, and finally pass those results into your indexer.

This MCP Server works with any client supporting tool specification. You connect it via the Vinkius Marketplace, allowing you to add live data sources to your RAG pipeline.

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