How to Use the Gipuzkoa Irekia MCP in Pydantic AI

Q: Can I use Pydantic AI models with all Gipuzkoa Irekia tools?

Yes. Every tool, from listgroups to showresource, returns data that is validated against your schema. This ensures type safety across the board.

Get type-safe Gipuzkoa Irekia data in Pydantic AI with runtime validation for every response.

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Connect Gipuzkoa Irekia MCP to Pydantic AI

Create your Vinkius account to connect Gipuzkoa Irekia 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 Gipuzkoa Irekia with Pydantic AI

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Perplexity

Strictly typed data access

Every call to `list_packages` or `show_package` is checked against Pydantic models. If the Gipuzkoa API returns malformed data, your agent stops immediately. This prevents silent failures in your pipeline. You get a clear validation error, ensuring your agent only works with data that matches your expected schema.

Reliable search operations

Use `search_packages` to query the portal with confidence. Since the responses are validated at runtime, you never have to guess if a field is missing or incorrectly typed. This keeps your agent's logic robust. You define the structure, and the MCP server ensures the incoming data respects it.

Precise resource metadata

Retrieve resource details with `show_resource` and have them instantly cast to your Pydantic models. Your agent gets a clean, validated object to work with. It eliminates the need for manual parsing code. You spend your time building agent behavior instead of writing brittle data validation logic.

Setup guide

Set up Gipuzkoa Irekia 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": {
        "gipuzkoa-irekia-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Gipuzkoa Irekia MCP in Pydantic AI

Install the slim MCP package and use the MCPToolset class. Pass the server URL to your agent definition to start calling tools.

The MCP toolset will trigger a validation error. Your agent will fail loudly instead of proceeding with corrupt data, keeping your application state consistent.

Yes. Every tool, from `list_groups` to `show_resource`, returns data that is validated against your schema. This ensures type safety across the board.

The server supports Streamable HTTP and SSE. You can choose the transport that fits your deployment requirements for the Pydantic AI framework.

It enforces strict input and output validation. The server only exposes public Gipuzkoa Irekia data, and the validation layer prevents malicious or unexpected payloads from entering your memory.

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