SPTrans Olho Vivo MCP Server for LlamaIndexGive LlamaIndex instant access to 13 tools to Get All Positions, Get Forecast, Get Forecast By Line, and more
GDPR Free for SubscribersLlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add SPTrans Olho Vivo as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this MCP Server for LlamaIndex
The SPTrans Olho Vivo MCP Server for LlamaIndex 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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to SPTrans Olho Vivo. "
"You have 13 tools available."
),
)
response = await agent.run(
"What tools are available in SPTrans Olho Vivo?"
)
print(response)
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.
LlamaIndex agents combine SPTrans Olho Vivo tool responses with indexed documents for comprehensive, grounded answers. Connect 13 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex
When LlamaIndex 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 LlamaIndex via MCP
Follow these steps to wire SPTrans Olho Vivo into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the SPTrans Olho Vivo MCP Server
LlamaIndex provides unique advantages when paired with SPTrans Olho Vivo through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine SPTrans Olho Vivo tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain SPTrans Olho Vivo tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query SPTrans Olho Vivo, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what SPTrans Olho Vivo tools were called, what data was returned, and how it influenced the final answer
SPTrans Olho Vivo + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the SPTrans Olho Vivo MCP Server delivers measurable value.
Hybrid search: combine SPTrans Olho Vivo real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query SPTrans Olho Vivo to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying SPTrans Olho Vivo for fresh data
Analytical workflows: chain SPTrans Olho Vivo queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for SPTrans Olho Vivo in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting SPTrans Olho Vivo to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSPTrans Olho Vivo + LlamaIndex FAQ
Common questions about integrating SPTrans Olho Vivo MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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