How to Use the TomTom MCP in Pydantic AI

Q: Can TomTom handle traffic monitoring with Pydantic AI?

Yes. The toolset allows calling gettrafficflowsegment or gettrafficincidents. Because the outputs are validated, your agent knows that the reported speed and coordinates are structured correctly.

Q: What happens if I use TomTom with Pydantic AI for POI data?

When you call getpoidetails, the response is checked against a schema. You don't get unexpected fields or corrupted metadata, because Pydantic validates that every field exists and has the right type.

Build reliable agents guaranteed to output correct data using Pydantic AI and TomTom.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect TomTom MCP to Pydantic AI

Create your Vinkius account to connect TomTom 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.

GDPR Free for Subscribers

Setup TomTom with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Predictable Routing with the MCP Server

When calculating a route, the agent uses `calculate_route` and immediately validates the returned polyline and summary against your Pydantic models. Similarly, it determines reachable areas by calling `calculate_reachable_range`, ensuring the time budget is correctly structured. This prevents silent failures when dealing with complex geographic calculations.

Accurate Location Parsing for Pydantic AI

The framework makes parsing addresses safe. If you use `fuzzy_geocoding`, the resulting coordinates and address fields are validated before your agent uses them. This stops bad data from corrupting your output. If you need to find points of interest, calling `search_poi_by_category` returns a list whose structure is guaranteed by Pydantic.

Comprehensive Geocoding with TomTom and Pydantic AI

The agent can handle multiple geocoding inputs. It uses `structured_geocoding` for explicit components (like city/zip) or `fuzzy_geocoding` if the input is messy. The key benefit here is that every piece of coordinate data returned passes type checking. It also helps with general searches via `autocomplete_place_search`, ensuring predictive text matches expected formats.

Setup guide

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

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

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by TomTom. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect TomTom now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about TomTom MCP in Pydantic AI

The agent calls the MCP Server tools, and Pydantic validates every piece of data returned—like coordinates from `fuzzy_geocoding`. If the format is wrong, your agent fails loud, which is exactly what you want.

Yes. The toolset allows calling `get_traffic_flow_segment` or `get_traffic_incidents`. Because the outputs are validated, your agent knows that the reported speed and coordinates are structured correctly.

When you call `get_poi_details`, the response is checked against a schema. You don't get unexpected fields or corrupted metadata, because Pydantic validates that every field exists and has the right type.

The server provides core mapping services: route calculation (`calculate_route`), address conversion (both fuzzy and structured), real-time traffic data, and POI lookups.

The server handles coordinates, physical addresses, bounding box coordinates, and location IDs. These are all types of geographical identifiers that Pydantic AI validates for correctness.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript