SPTrans Olho Vivo MCP Server for CrewAIGive CrewAI instant access to 13 tools to Get All Positions, Get Forecast, Get Forecast By Line, and more
GDPR Free for SubscribersConnect your CrewAI agents to SPTrans Olho Vivo through Vinkius, pass the Edge URL in the `mcps` parameter and every SPTrans Olho Vivo tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
Ask AI about this MCP Server for CrewAI
The SPTrans Olho Vivo MCP Server for CrewAI 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
Geminifrom crewai import Agent, Task, Crew
agent = Agent(
role="SPTrans Olho Vivo Specialist",
goal="Help users interact with SPTrans Olho Vivo effectively",
backstory=(
"You are an expert at leveraging SPTrans Olho Vivo tools "
"for automation and data analysis."
),
# Your Vinkius token. get it at cloud.vinkius.com
mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)
task = Task(
description=(
"Explore all available tools in SPTrans Olho Vivo "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 13 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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.
When paired with CrewAI, SPTrans Olho Vivo becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call SPTrans Olho Vivo tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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 CrewAI 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 CrewAI
When CrewAI 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 CrewAI via MCP
Follow these steps to wire SPTrans Olho Vivo into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install CrewAI
pip install crewaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comCustomize the agent
role, goal, and backstory to fit your use caseRun the crew
python crew.py. CrewAI auto-discovers 13 tools from SPTrans Olho VivoWhy Use CrewAI with the SPTrans Olho Vivo MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with SPTrans Olho Vivo through the Model Context Protocol.
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
SPTrans Olho Vivo + CrewAI Use Cases
Practical scenarios where CrewAI combined with the SPTrans Olho Vivo MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries SPTrans Olho Vivo for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff
Scheduled intelligence reports: set up a crew that periodically queries SPTrans Olho Vivo, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain SPTrans Olho Vivo tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow
Compliance and audit automation: a compliance agent queries SPTrans Olho Vivo against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Example Prompts for SPTrans Olho Vivo in CrewAI
Ready-to-use prompts you can give your CrewAI 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 CrewAI
Common issues when connecting SPTrans Olho Vivo to CrewAI through Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
SPTrans Olho Vivo + CrewAI FAQ
Common questions about integrating SPTrans Olho Vivo MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.Can different agents in the same crew use different MCP servers?
mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.What happens when an MCP tool call fails during a crew run?
Can CrewAI agents call multiple MCP tools in parallel?
process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.Can I run CrewAI crews on a schedule (cron)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Explore More MCP Servers
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