How to Use the AEMO Australian Energy MCP in Mastra AI

Build automated energy workflows in Mastra AI using the AEMO Australian Energy MCP Server.

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…and any MCP-compatible client

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Connect AEMO Australian Energy MCP to Mastra AI

Create your Vinkius account to connect AEMO Australian Energy 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 AEMO Australian Energy with Mastra AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automated market response workflows

Trigger actions based on spot price spikes using `get_market_data` within your Mastra AI agent. If prices hit a threshold, your workflow executes the next step. Use `get_market_updates` to keep your team informed of grid news. The agent polls for social posts and updates automatically.

Facility-level energy management

Query specific generation units with `list_facilities` to map the current network status. Your agents use this to identify which sites are active. Check output performance for any plant like Bungala Solar with `get_facility_data`. It provides the raw numbers your agents need for logic branching.

Regional grid analysis

Group network data by state using `get_network_by_region` to tailor responses to local grid conditions. Your agents act on regional demand shifts instantly. Verify the renewable proportion of the grid via `get_renewable_proportion`. It allows your agents to make decisions based on the current energy mix.

Setup guide

Set up AEMO Australian Energy 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 AEMO Australian Energy 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: "aemo-australian-energy-mcp-client",
  servers: {
    "aemo-australian-energy-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent AEMO Australian Energy 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 OpenElectricity (OpenNEM). 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 AEMO Australian Energy MCP in Mastra AI

You add the Vinkius endpoint to your agent configuration. The MCP Server tools become available to your workflow engine immediately.

Yes, you can enable tool approval in your agent setup. This forces the agent to pause for your sign-off before executing critical actions.

The workflow engine handles retries automatically. If a request fails, the agent attempts to fetch the data again based on your defined backoff policy.

Your profile information stays within the secured Vinkius environment. The server only fetches what is necessary for your specific query.

Every request is ephemeral and processed in a V8-isolated sandbox. We clear all execution context after your workflow finishes, leaving no persistent footprint.

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