How to Use the ROAS Calculator MCP in Mastra AI

Q: Can I automate break-even point checks using Mastra AI?

Yes. You can build a robust workflow that calls calculatebreakevenroas. If its result is above the current ROAS, your agent automatically flags the spending as risky and notifies an admin.

Q: Does Mastra AI help benchmark my ad spend?

You can absolutely use gettargetbenchmark in a multi-step process. The workflow retrieves the industry standard, allowing you to compare it directly against your calculated ROAS.

Q: Is this MCP good for complex financial analysis with Mastra AI?

It's built for it. You can chain calculateroas and gettargetbenchmark together, ensuring that every step is verified before the final result is presented.

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Setup ROAS Calculator with Mastra AI

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Calculate overall ROAS and benchmarks.

The `calculate_roas` tool takes media spend and source revenue to determine your Return on Ad Spend. You can set up a workflow that runs this calculation automatically whenever new spending data comes in. This makes sure your ad performance metrics are always fresh, handling the math even if initial inputs fail or require retries.

Determine necessary break-even ROAS.

If you need to validate a new budget, run `calculate_break_even_roas`. This tool figures out the minimum Return on Ad Spend needed based on your contribution margin. You can build a multi-step flow: if the initial ROAS is below this calculated threshold, then trigger an admin notification and stop spending.

Get industry target benchmarks.

The `get_target_benchmark` tool fetches current target ROAS data for a specific vertical. This provides the necessary context when reviewing performance. Your complex workflow can use this benchmark to automatically compare against calculated results, flagging any significant deviations that need human review.

Setup guide

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

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

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

You wrap the tool calls inside a mastra agent workflow. You use conditional branching: if `calculate_roas` drops below X, then retry by calling `get_target_benchmark` for comparison.

It processes financial inputs like media spend and source revenue. The agent handles these as structured data types, making the calculation reliable even if retries are involved.

Yes. You can build a robust workflow that calls `calculate_break_even_roas`. If its result is above the current ROAS, your agent automatically flags the spending as risky and notifies an admin.

You can absolutely use `get_target_benchmark` in a multi-step process. The workflow retrieves the industry standard, allowing you to compare it directly against your calculated ROAS.

It's built for it. You can chain `calculate_roas` and `get_target_benchmark` together, ensuring that every step is verified before the final result is presented.

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