Bring Public Transit
to Pydantic AI
Learn how to connect SPTrans Olho Vivo to Pydantic AI and start using 13 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 SPTrans Olho Vivo MCP Server?
Connect to the SPTrans Olho Vivo API to bring real-time urban mobility intelligence to your AI agent. Monitor the entire São Paulo bus fleet and provide precise transit information through natural conversation.
What you can do
- Line & Stop Discovery — Search for bus lines by name or number and find specific stops by address or corridor.
- Real-time GPS Tracking — Fetch the exact coordinates of active buses on any given line or across the entire city fleet.
- Arrival Forecasts — Get accurate predictions for when the next bus will arrive at a specific stop or for all stops along a route.
- Corridor & Company Info — List intelligent bus corridors and operating companies to understand the city's transit infrastructure.
- Garage Status — Monitor vehicles currently in the garage for specific companies and lines.
How it works
- Subscribe to this server
- Enter your SPTrans Olho Vivo API Token
- Start querying São Paulo's transit system from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Commuters & Residents — Get instant updates on bus arrivals and locations without switching between multiple transit apps.
- Urban Planners & Researchers — Analyze real-time fleet distribution and corridor efficiency directly through AI-driven data extraction.
- Developers — Integrate São Paulo's transit data into workflows or tools using simple natural language commands.
Built-in capabilities (13)
Get real-time GPS positions for all active buses
Get arrival forecast for a specific stop and line
Get arrival forecast for all stops on a specific line
Get arrival forecast for all lines arriving at a specific stop
Get real-time GPS positions for buses on a specific line
Get real-time GPS positions for buses currently in the garage
List bus operating companies by area
List all intelligent bus corridors in São Paulo
Search for bus lines by number or name
Search for bus lines filtered by direction
Search for bus stops by name or address
Get all stops in a specific intelligent corridor
Get all stops for a specific bus line
Why Pydantic AI?
Pydantic AI validates every SPTrans Olho Vivo tool response against typed schemas, catching data inconsistencies at build time. Connect 13 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 SPTrans Olho Vivo 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 SPTrans Olho Vivo connection logic from agent behavior for testable, maintainable code
SPTrans Olho Vivo in Pydantic AI
SPTrans Olho Vivo and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect SPTrans Olho Vivo 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 SPTrans Olho Vivo in Pydantic AI
The SPTrans Olho Vivo 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 13 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
SPTrans Olho Vivo for Pydantic AI
Every tool call from Pydantic AI to the SPTrans Olho Vivo MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I find the specific code for a bus line?
Use the search_lines tool with the line number or name (e.g., '8000' or 'Lapa'). The agent will return the line code (cl), which is required for tracking positions or forecasts.
Can I see the arrival times for all buses at a particular stop?
Yes! Use the get_forecast_by_stop tool with the stop code (cp). It will list all upcoming bus arrivals for that location in real-time.
Is it possible to track the live location of buses on a map?
While the MCP returns raw coordinates, you can use get_positions_by_line to get the latitude and longitude of every active bus on a line, which your AI can then describe or plot.
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 SPTrans Olho Vivo 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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