How to Use the Unit Economics Calculator MCP in Pydantic AI

Guaranteed correct unit economics analysis using the Pydantic AI framework.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Unit Economics Calculator MCP to Pydantic AI

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

GDPR Included with Plan

Setup Unit Economics Calculator with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Unit Economics Calculator for Pydantic AI

The biggest win here is data certainty. This MCP suite calculates your LTV components and runs through `calculate_contribution_margin`. Every response is validated against a strict schema, so you never get hallucinated fields. It determines gross profit per customer by ensuring all inputs for revenue and variable costs are correct before computation.

Type-Safe Financial Modeling

Need to know the payback period? The `calculate_payback_period` tool runs reliably because Pydantic validates its inputs. This prevents agents from failing silently when handling complex time-based cash flow models. Correctness matters more than speed here, and this MCP guarantees it.

Validated Health Checks

The `rate_health` tool assesses unit economics health. Because the entire process is type-checked, you get a guaranteed, structured report on your LTV:CAC ratio. Your agent receives an unambiguous result that it can trust and act upon immediately.

Setup guide

Set up Unit Economics Calculator MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "unit-economics-calculator-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Unit Economics Calculator tools.",
)

result = await agent.run("List recent Unit Economics Calculator transactions")
print(result.output)

Get your connection token →

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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Unit Economics Calculator now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Unit Economics Calculator MCP in Pydantic AI

The MCP ensures that every time your agent calls the tools, the resulting data is validated against a strict schema. This eliminates bad or unexpected output.

It processes standard financial inputs: revenue figures, variable cost data for contribution margin, and customer acquisition spend needed for payback modeling.

Absolutely. The runtime validation means that if the API returns bad data, your agent fails loudly with a specific error—no silent corruption.

Yes. Since every tool call is validated and structured, you have an ironclad record of exactly what data flowed through to get your final ratio.

The server handles structured financial metrics: revenue amounts, cost inputs for contribution margin calculation, and customer acquisition spend history.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript