Bring Railway
to Pydantic AI
Learn how to connect Renfe Data to Pydantic AI and start using 11 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 Renfe Data MCP Server?
Connect to the Renfe Data portal to monitor the Spanish railway network in real-time. This server provides comprehensive access to both live operational data and static historical datasets through the official CKAN infrastructure.
What you can do
- Real-time Tracking — Get precise GPS locations and movement status for Cercanías (commuter) and Long Distance (AVE/LD/MD) trains.
- Trip Updates & Delays — Monitor live delays, cancellations, and platform changes to keep travelers informed.
- CKAN Portal Access — List, search, and inspect metadata for thousands of railway datasets and resources.
- Service Alerts — Retrieve real-time information on accessibility issues, track incidents, or bus substitutions.
- Static Schedules — Fetch direct download URLs for GTFS schedules and station lists for offline analysis.
How it works
- Subscribe to this server
- Enter your Renfe Data API Key
- Start querying Spanish railway data from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Logistics & Transport Analysts — track fleet movements and analyze network performance metrics.
- Travel App Developers — integrate real-time Spanish train data and GTFS schedules into custom applications.
- Data Scientists — access open government data for urban mobility research and visualization.
Built-in capabilities (11)
Search for data within a resource
List all dataset names in Renfe Data
Get metadata for a specific dataset
Get metadata for a specific resource
Get planned service modifications (Avisos)
List URLs for static datasets (Schedules & Stations)
Updates every 20 seconds. Get real-time service alerts for Cercanías
Updates every 20 seconds. Get real-time trip updates for Cercanías
Updates every 30 seconds. Get real-time trip updates for AV / LD / MD
Updates every 20 seconds. Get real-time vehicle positions for Cercanías
Updates every 15 minutes. Get real-time vehicle positions for AV / LD / MD
Why Pydantic AI?
Pydantic AI validates every Renfe Data tool response against typed schemas, catching data inconsistencies at build time. Connect 11 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 Renfe Data 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 Renfe Data connection logic from agent behavior for testable, maintainable code
Renfe Data in Pydantic AI
Renfe Data and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Renfe Data 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 Renfe Data in Pydantic AI
The Renfe Data 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 11 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
Renfe Data for Pydantic AI
Every tool call from Pydantic AI to the Renfe Data MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How often are the real-time train positions updated?
It depends on the service: Cercanías positions (rt_vehicle_positions_cercanias) update every 20 seconds, while Long Distance trains (rt_vehicle_positions_ld) update every 15 minutes.
Can I check for delays or platform changes for a specific trip?
Yes. Use rt_trip_updates_cercanias or rt_trip_updates_ld to get live information on delays, cancellations, and platform assignments across the network.
Where can I find the static GTFS files for schedules?
You can use the get_static_datasets tool. It returns direct download URLs for GTFS schedule packages and CSV/XLSX lists of all Renfe stations.
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 Renfe Data 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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