How to Use the World Bank Education & Health MCP in Mastra AI

Q: How does Mastra AI handle World Bank Education & Health data retrieval?

You wrap tool calls like geteduhealthindicator inside a workflow step. This allows you to define retries and fallbacks, ensuring that even if the initial attempt fails, your process continues until it gets the required social welfare statistics.

Q: Can I build complex workflows with World Bank Education & Health metrics using Mastra AI?

Yes. You can create conditional logic: if gethealthexpenditure exceeds X, then run an alert workflow. This makes your pipelines much more powerful than simple script execution.

Build Resilient Workflows for World Bank Education & Health Data with Mastra AI.

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Connect World Bank Education & Health MCP to Mastra AI

Create your Vinkius account to connect World Bank Education & Health to Mastra AI 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 Mastra AI

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Perplexity

Orchestrating Indicator Lookups

The `get_edu_health_indicator` tool lets your workflow fetch any World Bank education or health indicator using a specific code. Because you're building complex, multi-step processes with Mastra AI, this call can be wrapped in conditional logic. If the initial indicator lookup fails, your workflow doesn't crash. It automatically retries the request or switches to pulling general metrics like `get_life_expectancy` instead.

Managing Expenditure and Rates

Need to compare spending? The `get_health_expenditure` tool gets current health expenditure (% of GDP). Mastra AI handles the complexity here: you can set up a step that checks if the data is available, waits for it, and then moves on. This guarantees your entire pipeline runs reliably. You don't have to babysit the process when fetching crucial social welfare statistics.

Sequential Data Gathering

Run a sequence of checks like `get_infant_mortality` followed by `get_literacy_rate`. Mastra AI's built-in workflow engine ensures that the second step only runs after the first completes successfully. This is crucial for building accurate reports. It manages failure gracefully, meaning if one rate check fails, you get a clean error notification instead of a broken job.

Setup guide

Set up World Bank Education & Health MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All World Bank Education & Health tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "world-bank-education-health-mcp-client",
  servers: {
    "world-bank-education-health-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "World Bank Education & Health Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to World Bank Education & Health tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent World Bank Education & Health transactions"
);
console.log(result.text);

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by World Bank Open Data. 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 World Bank Education & Health MCP in Mastra AI

You wrap tool calls like `get_edu_health_indicator` inside a workflow step. This allows you to define retries and fallbacks, ensuring that even if the initial attempt fails, your process continues until it gets the required social welfare statistics.

You access global data like life expectancy, infant mortality rates, and adult literacy rates. Since these are read-only indicators, the focus is on reliable extraction into a structured output.

Yes. You can create conditional logic: if `get_health_expenditure` exceeds X, then run an alert workflow. This makes your pipelines much more powerful than simple script execution.

The server only retrieves public global statistics—specific indicators and rates. The primary data type is aggregated social welfare statistics, so there's no sensitive user PII involved.

Mastra AI supports automatic retries with exponential backoff. If `get_life_expectancy` times out, the system waits and tries again, ensuring data integrity without manual intervention.

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