How to Use the WHO Athena API MCP in Mastra AI

Q: Which tools can I expose from WHO Athena API to Mastra AI?

You can pass all four available tools: gethealthindicatordata, listhealthindicators, and the metadata listing functions. The developer chooses which ones are necessary for a specific workflow.

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Connect WHO Athena API MCP to Mastra AI

Create your Vinkius account to connect WHO Athena API 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 WHO Athena API with Mastra AI

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Execute Multi-Step Data Retrieval

Use `get_health_indicator_data` to pull specific global statistics for a defined indicator code. Your Mastra AI workflow can sequence this call, then use the returned data in subsequent steps—maybe cross-referencing it with other internal records. This is key for building complex operational pipelines. If one piece of data fails or needs validation, your framework handles retries and conditional branching automatically.

Pre-flight Data Validation

Before running a full report, run `list_health_dimensions` to confirm the required observation dimensions are available. This prevents workflow failure because it validates the input parameters needed for success. This pre-check is critical in high-stakes automation. The system confirms that country codes and year ranges are valid before committing resources.

Catalog All Data Sources

Need to know what metrics exist? Calling `list_health_indicators` provides a full list of available WHO health indicator codes for your workflow engine. This allows the agent to build internal decision trees. Your Mastra AI setup uses this catalog output to inform its next step, ensuring it only attempts to process valid indicators.

Setup guide

Set up WHO Athena API 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 WHO Athena API 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: "who-athena-api-mcp-client",
  servers: {
    "who-athena-api-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "WHO Athena API Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to WHO Athena API tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent WHO Athena API 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 WHO Athena. 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 Athena API MCP in Mastra AI

The MCP Server provides the core data source for your workflow. Mastra AI executes multi-step actions, using tools like `get_health_indicator_data` as nodes in its graph. The system manages sequencing and failure recovery.

It handles structured global health indicator data, including indicators, observation dimensions (like country/year), and the associated metrics. It's designed for programmatic access to large datasets.

Yes. The built-in workflow engine supports automatic retries with exponential backoff. If a specific tool call, like `check_api_status`, fails temporarily, the system doesn't just halt; it tries again.

You can pass all four available tools: `get_health_indicator_data`, `list_health_indicators`, and the metadata listing functions. The developer chooses which ones are necessary for a specific workflow.

It touches global health indicator data, including structured metrics tied to indicators and dimensions. This is the operational data your workflows rely on.

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