SPTrans Olho Vivo MCP Server for Pydantic AIGive Pydantic AI instant access to 13 tools to Get All Positions, Get Forecast, Get Forecast By Line, and more
GDPR Free for SubscribersPydantic AI brings type-safe agent development to Python with first-class MCP support. Connect SPTrans Olho Vivo 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 SPTrans Olho Vivo MCP Server for Pydantic AI is a standout in the Data Analytics category — giving your AI agent 13 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport 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 SPTrans Olho Vivo "
"(13 tools)."
),
)
result = await agent.run(
"What tools are available in SPTrans Olho Vivo?"
)
print(result.data)
asyncio.run(main())
* 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 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.
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.
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.
The SPTrans Olho Vivo MCP Server exposes 13 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 13 SPTrans Olho Vivo tools available for Pydantic AI
When Pydantic AI connects to SPTrans Olho Vivo through Vinkius, your AI agent gets direct access to every tool listed below — spanning public-transit, real-time-tracking, gps-data, 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.
Get all positions on SPTrans Olho Vivo
Get real-time GPS positions for all active buses
Get forecast on SPTrans Olho Vivo
Get arrival forecast for a specific stop and line
Get forecast by line on SPTrans Olho Vivo
Get arrival forecast for all stops on a specific line
Get forecast by stop on SPTrans Olho Vivo
Get arrival forecast for all lines arriving at a specific stop
Get positions by line on SPTrans Olho Vivo
Get real-time GPS positions for buses on a specific line
Get positions in garage on SPTrans Olho Vivo
Get real-time GPS positions for buses currently in the garage
List companies on SPTrans Olho Vivo
List bus operating companies by area
List corridors on SPTrans Olho Vivo
List all intelligent bus corridors in São Paulo
Search lines on SPTrans Olho Vivo
Search for bus lines by number or name
Search lines by direction on SPTrans Olho Vivo
Search for bus lines filtered by direction
Search stops on SPTrans Olho Vivo
Search for bus stops by name or address
Search stops by corridor on SPTrans Olho Vivo
Get all stops in a specific intelligent corridor
Search stops by line on SPTrans Olho Vivo
Get all stops for a specific bus line
Connect SPTrans Olho Vivo to Pydantic AI via MCP
Follow these steps to wire SPTrans Olho Vivo into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the SPTrans Olho Vivo MCP Server
Pydantic AI provides unique advantages when paired with SPTrans Olho Vivo through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your SPTrans Olho Vivo integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your SPTrans Olho Vivo connection logic from agent behavior for testable, maintainable code
SPTrans Olho Vivo + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the SPTrans Olho Vivo MCP Server delivers measurable value.
Type-safe data pipelines: query SPTrans Olho Vivo with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple SPTrans Olho Vivo tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query SPTrans Olho Vivo and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock SPTrans Olho Vivo responses and write comprehensive agent tests
Example Prompts for SPTrans Olho Vivo in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with SPTrans Olho Vivo immediately.
"Search for bus lines related to 'Lapa'."
"What are the arrival forecasts for stop code 650005666?"
"Show me the real-time positions of buses on line 33657."
Troubleshooting SPTrans Olho Vivo MCP Server with Pydantic AI
Common issues when connecting SPTrans Olho Vivo to Pydantic AI through Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiSPTrans Olho Vivo + Pydantic AI FAQ
Common questions about integrating SPTrans Olho Vivo MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
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