How to Use the Geometry Calculator MCP in Pydantic AI

Enforce strict type-safety for all spatial math in your Pydantic AI agents.

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Connect Geometry Calculator MCP to Pydantic AI

Create your Vinkius account to connect Geometry Calculator to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Geometry Calculator with Pydantic AI

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Type-safe geometry for Pydantic AI

Every call to `calculate_distance` is validated against your Pydantic models at runtime. You get immediate feedback if your agent provides malformed coordinate data. This prevents silent errors in your agent pipeline. If the input doesn't match the schema, the agent stops before executing faulty math.

Strictly typed 3D volumes in Pydantic AI

The `calculate_3d_volume` tool ensures your agent's dimensional math is always valid. By forcing runtime validation, you eliminate the risk of hallucinated fields or incorrect parameters. Your agent logic becomes predictable and reliable. You know exactly what data format the tools expect, and the Pydantic AI framework enforces it.

Validated 2D area calculations

Use `calculate_2d_area` with full schema enforcement. Your Pydantic AI agent will only pass valid radius or base-height pairs, ensuring the math is always correct. It’s the safest way to handle geometry in a production environment. You get the speed of local execution combined with the rigor of type-safe code.

Setup guide

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

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

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

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Common questions about Geometry Calculator MCP in Pydantic AI

Pydantic AI uses its internal model definition to verify the MCP server output. If the geometry tool returns unexpected data, the framework triggers a validation error immediately.

Yes. Since Pydantic AI is model-agnostic, you can swap your underlying LLM without changing how you interact with the geometry tools. The type-safety remains constant.

You use the MCPToolset class to connect the server. It’s a clean, unified approach that integrates directly into your agent setup without extra boilerplate code.

Pydantic AI will catch the mismatch between your input and the expected schema. You'll receive a clear validation error, preventing the tool from running with bad data.

The server operates locally, and Pydantic AI ensures your data structure is strictly controlled. No geometric input is sent to external services, ensuring total privacy for your calculations.

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