How to Use the TomTom Parking Availability MCP in Pydantic AI

Q: How does TomTom Parking Availability work with Pydantic AI?

The framework wraps the MCP calls (like searchparkingspots) and forces every output to match a defined Python schema. This means your agent always receives clean, predictable data types.

Q: What if I need detailed info about one spot using TomTom Parking Availability with Pydantic AI?

You call getparkingdetails and pass the ID. The result is instantly validated, giving you confidence that every field—from capacity to specific notes—is correctly structured.

Q: Does TomTom Parking Availability support failure checks when using Pydantic AI?

Yes. You can use checkapistatus and trust the result because its output is validated against your defined schema, confirming both operational status and data structure.

Guarantee Correctness: TomTom Parking Availability with Pydantic AI for Type Safety.

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Connect TomTom Parking Availability MCP to Pydantic AI

Create your Vinkius account to connect TomTom Parking Availability 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 TomTom Parking Availability with Pydantic AI

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Validate Service Status

The `check_api_status` tool verifies the operational status of the parking service. With Pydantic AI, you get a schema-validated response confirming if the API is reachable. If the underlying data structure changes unexpectedly, your agent fails loudly with an error—you never risk silent corruption or bad data.

Get Type-Safe Spot Details

Use `get_parking_details` to retrieve full metadata for a specific ID. Since every response validates against Pydantic models, you're guaranteed that fields like 'capacity' or 'address' will be present and the correct type. This eliminates the risk of consuming an API field that suddenly changes its format, which is critical when correctness matters more than speed.

Search with Guaranteed Output

`search_parking_spots` finds spots by location. The Pydantic wrapper ensures the list returned—the coordinates, IDs, and availability status—matches your expected schema. If the server delivers garbage data, your agent throws a clear validation error immediately. You know exactly where it broke.

Setup guide

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

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

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

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Common questions about TomTom Parking Availability MCP in Pydantic AI

The framework wraps the MCP calls (like `search_parking_spots`) and forces every output to match a defined Python schema. This means your agent always receives clean, predictable data types.

The server exposes location metadata, including IDs and coordinates, alongside availability status. These fields are strictly typed by the framework to ensure runtime reliability for your application logic.

You can. The primary benefit is that it guarantees data integrity at the point of consumption. If the API deviates, your agent fails gracefully with a clear validation exception.

You call `get_parking_details` and pass the ID. The result is instantly validated, giving you confidence that every field—from capacity to specific notes—is correctly structured.

Yes. You can use `check_api_status` and trust the result because its output is validated against your defined schema, confirming both operational status and data structure.

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