Bring Open Data
to Pydantic AI
Learn how to connect Open Data Euskadi to Pydantic AI and start using 2 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Open Data Euskadi MCP Server?
Connect to the Open Data Euskadi ecosystem and interact with the Basque Government's official public data through natural conversation. This server provides direct access to a vast catalog of administrative and semantic information.
What you can do
- Content Search — Query the Euskadi.eus catalog for grants, public contracts, news, and administrative procedures using advanced filters.
- Linked Open Data (LOD) — Execute raw SPARQL queries against the GraphDB endpoint to retrieve structured RDF data for deep analysis.
- Administrative Transparency — Access real-time information on public announcements, board notices, and governmental publications.
- Meteorological Data — Retrieve specialized datasets, including weather information from Euskalmet when authorized.
- Metadata Filtering — Narrow down results by language, date ranges, and specific portal contexts to find exactly what you need.
How it works
- Subscribe to this server
- Enter your Euskalmet JWT (optional for public data)
- Start querying Basque public data from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Data Analysts & Researchers — perform complex semantic queries across public datasets without manual exports
- Legal & Administrative Professionals — track public grants, subsidies, and government contracts in real-time
- Developers — integrate official Basque government data and news feeds directly into your AI-driven workflows
Built-in capabilities (2)
Execute a SPARQL query against Open Data Euskadi
Search the Euskadi.eus content catalog
Why Pydantic AI?
Pydantic AI validates every Open Data Euskadi tool response against typed schemas, catching data inconsistencies at build time. Connect 2 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.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Open Data Euskadi integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your Open Data Euskadi connection logic from agent behavior for testable, maintainable code
Open Data Euskadi in Pydantic AI
Open Data Euskadi and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Open Data Euskadi to Pydantic AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Open Data Euskadi in Pydantic AI
The Open Data Euskadi 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. All 2 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Open Data Euskadi for Pydantic AI
Every tool call from Pydantic AI to the Open Data Euskadi MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I filter content by a specific language or date range?
You can use the metadata_filters parameter in the search_euskadi_content tool. For example, use documentLanguage.EQ.es for Spanish or procedureStartDate.BETWEEN.01/01/2023,31/12/2023 for dates.
Can I perform advanced semantic analysis on the data?
Yes! Use the execute_sparql_query tool to run raw SPARQL queries against the Linked Open Data (LOD) endpoint. This allows you to traverse relationships in the RDF graph directly.
What types of administrative content can I search for?
The search_euskadi_content tool allows you to filter by content_type. Common types include ayuda_subvencion (grants), contratacion (contracts), noticia (news), and anuncio_tablon (board notices).
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.
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.
Can I switch LLM providers without changing MCP code?
Absolutely. Pydantic AI abstracts the model layer. your Open Data Euskadi MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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