How to Use the Unit Economics Calculator MCP in OpenAI Agents SDK

Instantly determine unit economics profitability using your OpenAI Agents SDK agent.

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Connect Unit Economics Calculator MCP to OpenAI Agents SDK

Create your Vinkius account to connect Unit Economics Calculator to OpenAI Agents SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Unit Economics Calculator with OpenAI Agents SDK

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Unit Economics Calculator for OpenAPI Agents SDK

Need to know if a customer acquisition strategy actually makes money? This MCP suite calculates the core components of your business model. You can determine gross profit per customer using `calculate_contribution_margin`, which takes revenue and variable costs into account. It also figures out how long it takes for a new customer to pay back their cost, running through the `calculate_payback_period` tool. This gives you crucial data points before making any big spend.

Health Checks and Financial Modeling

The system doesn't just spit out numbers; it tells you if your unit economics are actually healthy. The `rate_health` tool assesses overall profitability based on the payback period. This helps you quickly check if your current growth rate is sustainable or if you need to adjust pricing and spending immediately.

Complex Financial Tracing

When building a production agent system, you can't afford guesswork. This MCP lets your agents run interconnected financial models that track LTV, CAC, and the resulting ratio. It’s designed for safety constraints, ensuring every calculation is validated before your deployed product acts on it.

Setup guide

Set up Unit Economics Calculator MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Unit Economics Calculator tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Unit Economics Calculator tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Unit Economics Calculator tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Unit Economics Calculator Agent",
            instructions="You have access to Unit Economics Calculator tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 Unit Economics 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 Unit Economics Calculator MCP in OpenAI Agents SDK

Your agent calls the MCP tools directly. You pass in variables like revenue and costs, and the system returns a clear assessment of your financial health.

This server handles standard financial metrics, including revenue figures, variable cost inputs, and customer acquisition spend data.

Yes. The MCP is built to run within production agent systems, providing guarded tool calls that maintain integrity across complex workflows.

By calculating key ratios like LTV:CAC and assessing payback periods, it flags potential financial risks before they become actual operational losses.

The system guarantees reliable output because your agent uses structured tool calls that validate inputs and process data step-by-step.

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