How to Use the Dades Obertes Catalunya MCP in Pydantic AI

Q: How do I add Dades Obertes Catalunya to Pydantic AI?

Use the MCPToolset class in your agent definition. It connects to the server and makes the tools available for the model.

Q: Can my Pydantic AI agent search Dades Obertes Catalunya?

Absolutely. It uses the searchcatalog tool to find the right dataset before querying.

Get type-safe Catalonia open data inside your Pydantic AI agent.

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Connect Dades Obertes Catalunya MCP to Pydantic AI

Create your Vinkius account to connect Dades Obertes Catalunya 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 Dades Obertes Catalunya with Pydantic AI

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Claude

Perplexity

Find datasets for Pydantic AI

The `search_catalog` tool returns the IDs your agent needs to fetch data. It acts as the discovery layer for your Pydantic-validated logic. Your agent gets clear results from the catalog. This ensures it knows exactly which dataset to target for the next step.

Pydantic AI queries with SoQL

Run `query_dataset` to extract records into your application. Since you are using Pydantic AI, you can validate these responses against your models. This prevents bad data from reaching your logic. Any structure mismatch triggers a validation failure immediately.

Type-safe MCP server connection

Connect the server via `MCPToolset` to your agent. It integrates into your existing async pipeline with full runtime validation. Your agent uses these tools with total type safety. It keeps your data processing strict and predictable.

Setup guide

Set up Dades Obertes Catalunya 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": {
        "dades-obertes-catalunya-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Dades Obertes Catalunya transactions")
print(result.output)

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Common questions about Dades Obertes Catalunya MCP in Pydantic AI

Yes. You define your Pydantic models, and the agent checks incoming data against them. If the data is malformed, the agent reports an error.

Use the `MCPToolset` class in your agent definition. It connects to the server and makes the tools available for the model.

Absolutely. It uses the `search_catalog` tool to find the right dataset before querying.

It is. The tools are designed to work with the standard toolset interface provided by the framework.

The server interacts only with public, open-access datasets. Your agent's runtime environment remains protected by Pydantic's strict type enforcement on all incoming information.

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