How to Use the Roast Calculator MCP in Mastra AI

Build resilient, multi-step roasting workflows and automated rest timers with Mastra AI.

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Connect Roast Calculator MCP to Mastra AI

Create your Vinkius account to connect Roast Calculator to Mastra AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Roast Calculator with Mastra AI

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Build automated cooking workflows with this MCP Server

We use `calculate_cooking_duration` to calculate how long a roast needs to stay in the oven based on mass and heat. Roasting is a multi-step thermodynamic process that requires strict timing. Mastra AI lets you chain steps together, running the estimation to set the timeline. If the oven heat fluctuates, the workflow triggers a recalculation automatically.

Handle carryover spikes using Mastra AI conditional paths

The `estimate_carryover_impact` tool predicts the exact thermal spike that occurs after you pull the meat. Watch the carryover, or you'll ruin a prime cut of Wagyu. Mastra AI handles branching decisions based on real-time heat data. The workflow decides whether to prompt the cook to vent the oven or pull the meat early.

Program safe resting buffers with Mastra AI

Our `calculate_rest_duration` tool determines the exact resting buffer required to let muscle fibers relax. Juices must redistribute, and that is the basic science of meat. Use this within an agent workflow to hold the next step until the meat is cool enough. The framework handles the timing and triggers the final carving alert.

Setup guide

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

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

const result = await agent.generate(
  "List recent Roast Calculator 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 Roast Calculator. 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 Roast Calculator MCP in Mastra AI

Instantiate the MCPClient with the server's URL. Then, call listTools and spread the resulting tools directly into your Mastra agent configuration.

Yes, the framework features built-in exponential backoff. If a connection blip occurs during a calculation, Mastra AI retries the request automatically.

Use the Mastra workflow engine to define steps for cooking, resting, and carving. This MCP provides the mathematical inputs needed to trigger conditional transitions between those steps.

Yes, you can configure the framework to require manual approval before moving from the cooking phase to the resting phase.

Your oven temperatures, target internal heat, and meat weights are processed locally within your agent's runtime. No cooking telemetry is sent to third-party databases.

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