How to Use the Basis Calculator MCP in Pydantic AI

Get type-safe commodity basis analysis in Pydantic AI for reliable, validated agent operations.

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Connect Basis Calculator MCP to Pydantic AI

Create your Vinkius account to connect Basis 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 Basis Calculator with Pydantic AI

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Type-validated basis math

Use `calculate_current_basis` to get firm, validated numbers for your pricing models. Every response is checked against Pydantic models to ensure the data is exactly what your agent expects. This prevents errors that come from malformed API responses. Your agent operates on clean, verified data at every step.

Verify against historical data

Query `get_historical_averages` to get verified trailing data for your region. The agent validates these figures against predefined types, ensuring zero silent data corruption. This approach gives you confidence in the agent's logic. If the data doesn't match the expected schema, the process fails immediately rather than proceeding with bad info.

Monitor seasonality with confidence

Apply `get_seasonality_trend` to see how the market usually moves this time of year. Because this is Pydantic AI, the output is strictly typed and ready for immediate use in your logic. This makes your agent's reasoning transparent and predictable. You avoid the risks of hallucinated fields or unexpected data formats when planning your market moves.

Setup guide

Set up Basis 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": {
        "basis-calculator-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Basis Calculator MCP in Pydantic AI

Install the slim package and define your toolset using the HTTP endpoint. Once registered, pass the toolset to your agent to begin using the validated functions.

Pydantic AI enforces strict runtime validation. This ensures that every calculation from the MCP is verified against your models before the agent acts on it.

It does. The toolset is designed for async operations, allowing your agent to gather basis data efficiently without blocking other tasks.

The framework will trigger a validation error. This protects your agent from acting on corrupt or unexpected data, keeping your system reliable.

Your input data is treated as a transient payload. The MCP processes it for the calculation and returns only the result, keeping your private pricing information isolated.

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