How to Use the Hedge Ratio Calculator MCP in Pydantic AI

Enforce strict type safety on your commodity math with Hedge Ratio Calculator and Pydantic AI.

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Connect Hedge Ratio Calculator MCP to Pydantic AI

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

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Setup Hedge Ratio Calculator with Pydantic AI

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Compute contract requirements via MCP Server

`calculate_hedge_volume` determines your required futures position based on physical inventory. Pydantic AI validates every single input and output against strict data models at runtime. If the server returns a float instead of an integer for contract counts, the framework fails loudly. You never execute a trade based on corrupted math.

Measure financial exposure with Pydantic AI

Call `evaluate_price_exposure` to calculate the cash at risk if the spot market collapses. The model-agnostic agent processes the result whether you run it locally or through a hosted provider. You get a verified number that your treasury team can trust. The strict validation ensures the exposure metric matches your exact schema requirements.

Forecast net profitability accurately

Send your market assumptions to `project_net_margin` and let the agent calculate your final harvest returns. The framework guarantees the final cash flow projection adheres to your financial models. You eliminate hallucinated numbers from your risk reports. The agent only proceeds when the mathematical outputs pass every validation check.

Setup guide

Set up Hedge Ratio 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": {
        "hedge-ratio-calculator-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Hedge Ratio Calculator transactions")
print(result.output)

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Common questions about Hedge Ratio Calculator MCP in Pydantic AI

Install the slim package with the MCP extra. Create an MCPToolset using the HTTP transport and pass it to your agent constructor.

The framework forces strict type checking on all financial outputs. Your agent will crash before it passes a hallucinated contract volume to your execution system.

Yes. The framework is completely model-agnostic. You can run the calculations through a local instance while maintaining full validation.

The framework throws a validation error immediately. You catch the bad data before it impacts your trading decisions.

The server processes your yield estimates and spot prices statelessly. The strict HTTP transport ensures your sensitive margin projections remain confined to your local execution environment.

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