How to Use the Awattar MCP in Mastra AI

Build complex energy automation workflows in Mastra AI. Handle price-driven tasks with automated retries and conditional logic.

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Connect Awattar MCP to Mastra AI

Create your Vinkius account to connect Awattar 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 Awattar with Mastra AI

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Perplexity

Automated pricing triggers for Mastra AI

Create agent workflows that react to `get_market_data` outputs. You can set conditional branches to initiate specific actions when electricity prices drop below a defined threshold. If the market data fetch times out, Mastra AI handles the retry automatically. It ensures your automation logic remains resilient even when external API conditions fluctuate.

Structured YAML for Mastra AI agents

Use `get_current_yaml` to feed structured energy statistics into your agent's memory. It provides the agent with the exact configuration needed to adjust smart home settings without manual intervention. This keeps your agent's decision-making process clean. It consumes the YAML directly, allowing for precise control over load-shifting operations.

Resilient energy task execution

Implement multi-step energy management tasks that rely on consistent data flow. The MCP server provides the raw market inputs, while your Mastra AI agent manages the task lifecycle from start to finish. It handles the logic of when to fetch data and when to act. You define the rules, and the agent executes them based on the incoming market stream.

Setup guide

Set up Awattar 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 Awattar 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: "awattar-mcp-client",
  servers: {
    "awattar-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Awattar transactions"
);
console.log(result.text);

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Common questions about Awattar MCP in Mastra AI

Add the server to your Mastra agent configuration via the MCP client. Once registered, `get_market_data` becomes a callable tool within your workflow definitions.

Yes, the server responds to standard requests which Mastra AI can wrap in its native retry logic. It ensures your energy data is always current.

Yes, you can script branches that execute specific hardware commands only when `get_market_data` returns a price below your target range.

Vinkius manages all authentication tokens. Your agent connects through a secure bridge, isolating your energy queries from unauthorized access.

The server retrieves electricity spot prices and home automation YAML schemas. It does not access your personal billing details or sensitive account credentials.

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