How to Use the LTV:CAC Calculator MCP in OpenAI Agents SDK

Know if your spending pays off. LTV:CAC Calculator for OpenAI Agents SDK.

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Works with every AI agent you already use

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MCP Servers — Included with Plan

Connect LTV:CAC Calculator MCP to OpenAI Agents SDK

Create your Vinkius account to connect LTV:CAC 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 LTV:CAC Calculator with OpenAI Agents SDK

Ask AI about this MCP

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Claude

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Validate Profitability with the MCP Server

Run `evaluate_profitability` to get a final verdict on your business model. This tool synthesizes the ratio, payback period, and overall financial health, telling you if scaling is smart. It’s built for production agents like yours. You can feed in raw channel spend data and watch your agent process it without worrying about silent failures.

Calculate Customer Acquisition Costs

Need to track costs per marketing stream? Use `calculate_cac`. Just give the tool an array of {channelName, totalSpend, newCustomersAcquired} objects, and it spits out the true CAC for each channel. This is critical when your agent has to hand off data between specialized services. It keeps every calculation clean and auditable.

Determine Customer Lifetime Value

Figure out what a customer's worth *after* the first purchase. `calculate_ltv` takes your ARPU, gross margin percentage, and churn rate to model LTV accurately. This calculation is key for building robust agent workflows that rely on predictable financial inputs.

Setup guide

Set up LTV:CAC 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 LTV:CAC Calculator tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives LTV:CAC 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 LTV:CAC 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="LTV:CAC Calculator Agent",
            instructions="You have access to LTV:CAC Calculator tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about LTV:CAC Calculator MCP in OpenAI Agents SDK

Your agent uses this MCP to calculate both CAC and LTV independently. Then, it passes those metrics into `evaluate_profitability` for a single, definitive ratio verdict.

It handles core financial metrics like total spend by channel (for CAC), average revenue per user (ARPU) and churn rates (for LTV). It's all about numbers.

Absolutely. You can set up a multi-step workflow where one specialized agent calculates CAC, and another feeds that output into the LTV calculation before the final verdict is generated.

This MCP touches financial metrics: floating-point numbers for spend/rates, integers for counts (customers), and strings for channel names.

It moves you beyond simple reporting. By calculating the full payback period and providing a verdict, it tells your agent *where* to focus investment next, not just how much was spent.

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