How to Use the Trimble MCP in Pydantic AI

Q: Can I use Pydantic AI for calculating tolls with Trimble?

Yes. The tool output from calculatetriptolls is validated by your schemas, ensuring you receive predictable fields for both cash and electronic toll fees in USD.

Q: Does Trimble support calculating state mileage with the MCP Server in Pydantic AI?

It does. The agent uses calculatestatemileage, and your schemas ensure that the returned data is properly broken down by US state or province.

Q: Can I use the MCP Server to calculate multiple routes with Pydantic AI?

You can. The agent uses calculatematrixrouting and receives a structured, validated output detailing distances and travel times between all your specified origins and destinations.

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Setup Trimble with Pydantic AI

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Validated Truck Routing with Pydantic AI

Your agent uses `calculate_truck_route` to get a validated, structured output containing the distance, time, and polyline for truck travel. This ensures you never deal with unexpected data formats. If your route needs special consideration (like avoiding certain roads), call `route_avoiding_roads`. The Pydantic AI framework validates that every necessary field is present in the resulting JSON.

Structured Geocoding and Location Search

Need an address? Run `reverse_geocode` to turn coordinates into a reliable commercial address, validated against your Pydantic schema. You can also search for specific places using `search_trimble_address`. Furthermore, the agent uses `route_by_vehicle_size`, which requires you to pass structured data (height/weight) and returns it in a predictable format.

Full Trip Logistics Calculation

The MCP Server lets your agent calculate total costs using `calculate_trip_tolls`—you'll get clean, validated fields for both cash and electronic fees. Want to know the scope of travel? Use `calculate_driving_isochrone` which provides structured data on reachable areas by time. Alternatively, you can use `calculate_matrix_routing` to get a clear, typed output of distances across many points.

Setup guide

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

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

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

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Common questions about Trimble MCP in Pydantic AI

It validates the tool outputs from the MCP Server. When your agent calls `calculate_truck_route`, it expects and verifies structured fields like distance, time, and the polyline.

Yes. The tool output from `calculate_trip_tolls` is validated by your schemas, ensuring you receive predictable fields for both cash and electronic toll fees in USD.

The server touches geographical location data—specific coordinates (lon/lat) and commercial street addresses—which are validated when running geocoding tools like `reverse_geocode`.

It does. The agent uses `calculate_state_mileage`, and your schemas ensure that the returned data is properly broken down by US state or province.

You can. The agent uses `calculate_matrix_routing` and receives a structured, validated output detailing distances and travel times between all your specified origins and destinations.

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