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Aragón Open Data MCP Server for Pydantic AIGive Pydantic AI instant access to 15 tools to Count Datasets, Get Dataset, Get Organization, and more

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Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Aragón Open Data through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this MCP Server for Pydantic AI

The Aragón Open Data MCP Server for Pydantic AI is a standout in the Knowledge Management category — giving your AI agent 15 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Aragón Open Data "
            "(15 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Aragón Open Data?"
    )
    print(result.data)

asyncio.run(main())
Aragón Open Data
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Aragón Open Data MCP Server

Connect to the Aragón Open Data portal and unlock a wealth of public information from the Government of Aragón. This MCP server allows your AI agent to browse, search, and analyze regional datasets, statistical views, and organizational metadata through natural language.

Pydantic AI validates every Aragón Open Data tool response against typed schemas, catching data inconsistencies at build time. Connect 15 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

  • Data Exploration — List all available views and datasets from the GA_OD_Core and CKAN catalogs.
  • Deep Data Preview — Fetch and preview actual records from specific views or resources with support for filtering and pagination.
  • Schema Inspection — Understand the structure of data by retrieving column names and data types for any specific view.
  • Advanced Search — Use Solr-powered queries to find specific datasets, tags, or organizations within the public catalog.
  • Publisher Insights — Retrieve detailed information about the organizations and themes (groups) that publish data in the region.

The Aragón Open Data MCP Server exposes 15 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 15 Aragón Open Data tools available for Pydantic AI

When Pydantic AI connects to Aragón Open Data through Vinkius, your AI agent gets direct access to every tool listed below — spanning open-data, aragon, ckan, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

count

Count datasets on Aragón Open Data

Get total dataset count

get

Get dataset on Aragón Open Data

Get dataset details

get

Get organization on Aragón Open Data

Get publisher/organization details

get

Get tag on Aragón Open Data

Get tag details

list

List datasets on Aragón Open Data

List all datasets (packages)

list

List groups on Aragón Open Data

List all themes/groups

list

List organizations on Aragón Open Data

List all publishers/organizations

list

List tags on Aragón Open Data

List all tags

list

List views on Aragón Open Data

List all available views in Aragón Open Data

most

Most downloaded datasets on Aragón Open Data

Get most downloaded datasets

newest

Newest datasets on Aragón Open Data

Get newest datasets

preview

Preview data on Aragón Open Data

By default, it returns the first 1000 records. Preview data from a view or resource

query

Query sparql on Aragón Open Data

Supports ontologies like EI2A, Aragopedia, ELI, and DataCube. Execute a SPARQL query

search

Search datasets on Aragón Open Data

Search for datasets

show

Show columns on Aragón Open Data

Get information about columns for a specific view

Connect Aragón Open Data to Pydantic AI via MCP

Follow these steps to wire Aragón Open Data into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 15 tools from Aragón Open Data with type-safe schemas

Why Use Pydantic AI with the Aragón Open Data MCP Server

Pydantic AI provides unique advantages when paired with Aragón Open Data through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Aragón Open Data integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Aragón Open Data connection logic from agent behavior for testable, maintainable code

Aragón Open Data + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Aragón Open Data MCP Server delivers measurable value.

01

Type-safe data pipelines: query Aragón Open Data with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Aragón Open Data tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Aragón Open Data and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Aragón Open Data responses and write comprehensive agent tests

Example Prompts for Aragón Open Data in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Aragón Open Data immediately.

01

"List all available data views in Aragón Open Data."

02

"Search for datasets related to 'turismo' in the catalog."

03

"Show me the first 5 records from the view with ID '702'."

Troubleshooting Aragón Open Data MCP Server with Pydantic AI

Common issues when connecting Aragón Open Data to Pydantic AI through Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Aragón Open Data + Pydantic AI FAQ

Common questions about integrating Aragón Open Data MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Aragón Open Data MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

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