How to Use the MotionTools MCP in Pydantic AI

Build type-safe, bulletproof logistics pipelines with Pydantic AI and the MotionTools MCP server.

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Connect MotionTools MCP to Pydantic AI

Create your Vinkius account to connect MotionTools 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 MotionTools with Pydantic AI

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Safe dispatching via the MotionTools MCP Server.

The `create_booking` tool forces strict type validation on every delivery order your agent submits. If the agent attempts to write a booking with missing parameters, the system raises a validation error before hitting the API. Reading data is just as secure. The agent calls `get_booking` or `list_bookings`, and Pydantic AI parses the JSON payload into typed Python models, eliminating silent data corruption.

Track drivers and vehicles with strict schemas

The `list_drivers` tool returns structured lists of your active operators. Your agent can query specific driver details with `get_driver`, knowing that phone numbers, names, and IDs match your internal types exactly. Vehicle data uses the same strict validation. The agent executes `list_vehicles` to check fleet status and `get_vehicle` to verify that truck dimensions and weight limits are properly formatted.

Validate service areas and customer profiles

The `list_service_areas` tool gives your agent a validated list of active operational zones. Before scheduling a run, the agent calls `get_service_area` to check geographic coordinates against the booking address. Customer details are managed through `list_customers`. This tool pulls customer records into typed Python objects, making it easy to cross-reference billing info with active delivery schedules.

Setup guide

Set up MotionTools 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": {
        "motiontools-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about MotionTools MCP in Pydantic AI

You initialize the MCPToolset with your Vinkius server URL and pass it to your agent. The framework automatically registers all ten tools and builds Pydantic schemas for them at runtime.

The framework raises a validation error immediately. This prevents your agent from operating on malformed driver or vehicle data, protecting your downstream logistics logic.

Yes. You can define a custom Pydantic model for address validation. Your agent run checks this model before executing the `create_booking` tool.

The integration supports both Streamable HTTP and SSE transports. Pydantic AI connects to the externally managed Vinkius MCP server over a secure, single-token connection.

All driver identities and customer profiles are transmitted over encrypted TLS connections. Vinkius operates as a zero-trust gateway, executing the server in an ephemeral sandbox.

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