How to Use the World Bank Education & Health MCP in OpenAI Agents SDK

Q: How do I check educational metrics using World Bank Education & Health and OpenAI Agents SDK?

You call geteduhealthindicator with the specific code for education. The agent returns a clean data object containing the indicator's value and associated metadata in one step.

Q: Can I get life expectancy using World Bank Education & Health and OpenAI Agents SDK?

Yes, simply use getlifeexpectancy. This tool retrieves the most recent global data for life expectancy at birth, allowing you to anchor your agent's analysis on a key demographic benchmark.

Q: What are the core stats available via World Bank Education & Health and OpenAI Agents SDK?

The MCP Server provides five main tools: indicators (geteduhealthindicator), health spending (gethealthexpenditure), infant mortality, life expectancy, and literacy rate. These cover a wide range of global social welfare metrics.

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Connect World Bank Education & Health MCP to OpenAI Agents SDK

Create your Vinkius account to connect World Bank Education & Health to OpenAI Agents SDK 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 World Bank Education & Health with OpenAI Agents SDK

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Fetch Specific World Bank Education & Health Metrics

Need a single indicator? The `get_edu_health_indicator` tool pulls any specific education or health statistic using its unique code. You get the data point right away, which is perfect for validating core inputs into your agent's decision flow. The SDK handles this call cleanly, allowing specialized agents to focus on analysis rather than data retrieval. This makes building complex workflows straightforward and dependable.

Analyze Demographic Trends with MCP Server

Compare life expectancy and infant mortality rates across multiple regions using separate calls for `get_life_expectancy` and `get_infant_mortality`. The agent can then synthesize these two metrics to calculate a basic demographic risk score. This combination of tools lets you build specialized comparison agents that don't need human intervention. You just define the goal, and your AI client retrieves the necessary global data points.

Model Socioeconomic Status with OpenAI Agents SDK

Figure out a region's overall socioeconomic health by pulling multiple stats: `get_literacy_rate` provides education metrics while `get_health_expenditure` shows financial commitment. Your agent combines these figures to give a holistic view. These tools let you move past single data points and model complex realities. You don't just get numbers; you get the input needed for meaningful, multi-variable analysis.

Setup guide

Set up World Bank Education & Health MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all World Bank Education & Health tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives World Bank Education & Health tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate World Bank Education & Health tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="World Bank Education & Health Agent",
            instructions="You have access to World Bank Education & Health tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about World Bank Education & Health MCP in OpenAI Agents SDK

You call `get_edu_health_indicator` with the specific code for education. The agent returns a clean data object containing the indicator's value and associated metadata in one step.

Yes, simply use `get_life_expectancy`. This tool retrieves the most recent global data for life expectancy at birth, allowing you to anchor your agent's analysis on a key demographic benchmark.

The MCP Server provides five main tools: indicators (`get_edu_health_indicator`), health spending (`get_health_expenditure`), infant mortality, life expectancy, and literacy rate. These cover a wide range of global social welfare metrics.

Absolutely. Because tools are auto-discovered, your agent can sequence calls—for example, getting `get_infant_mortality` first and then using that result to inform a call for `get_literacy_rate`. It's designed for multi-step reasoning.

The server primarily touches global demographic and social welfare statistics, including indicators, mortality rates, and literacy percentages. This is aggregate, public domain data for modeling purposes.

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