TripGo MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add TripGo as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import 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 TripGo. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in TripGo?"
)
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 TripGo MCP Server
What you can do
Connect AI agents to the TripGo platform for intelligent multimodal journey planning:
LlamaIndex agents combine TripGo tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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.
- Plan trips combining bus, train, subway, tram, ferry, walking, and cycling
- Find nearby transit stops by GPS coordinates with distance and route info
- Search stops by name or address for precise location discovery
- Get real-time departures and arrivals with live delay estimates
- Track vehicle positions on the map with real-time GPS data
- Review route information including all stops and agency details
- Check stop details with accessibility and amenity information
- Access global regions covering major cities worldwide
The TripGo MCP Server exposes 9 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect TripGo to LlamaIndex via MCP
Follow these steps to integrate the TripGo MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 9 tools from TripGo
Why Use LlamaIndex with the TripGo MCP Server
LlamaIndex provides unique advantages when paired with TripGo through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine TripGo tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain TripGo tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query TripGo, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what TripGo tools were called, what data was returned, and how it influenced the final answer
TripGo + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the TripGo MCP Server delivers measurable value.
Hybrid search: combine TripGo real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query TripGo 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 TripGo for fresh data
Analytical workflows: chain TripGo queries with LlamaIndex's data connectors to build multi-source analytical reports
TripGo MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect TripGo to LlamaIndex via MCP:
get_arrivals
Returns route names, origins, scheduled vs estimated arrival times, and delays. Use this to track incoming vehicles. Requires stop ID. Get upcoming arrivals to a transit stop
get_departures
Returns route names, destinations, scheduled vs estimated departure times, and delays. Use this to check when your next ride arrives. Requires stop ID. Get upcoming departures from a transit stop
get_nearby_stops
Returns stop IDs, names, coordinates, routes serving each stop, and distance from search point. Use this to find nearest transit options before planning trips. Find transit stops near a GPS coordinate
get_regions
Each region has an ID, name, and coverage area. Use this first to verify your city is covered before planning trips. Supports major cities across North America, Europe, Australia, and Asia. List all available transit regions supported by TripGo
get_route_info
Requires route ID. Use this to understand route coverage before planning trips. Get information about a specific transit route
get_stop_details
Requires stop ID from nearby stops or search results. Use this to review stop facilities before waiting there. Get detailed information about a specific transit stop
get_vehicle_positions
Optionally filter by route ID. Use this for real-time tracking of vehicles on the map. Get real-time vehicle positions for transit vehicles
plan_trip
Combines public transport (bus, train, subway, tram, ferry) with walking and cycling. Returns multiple trip options with departure/arrival times, duration, number of transfers, and step-by-step instructions. Optionally specify travel time and preferred transport modes. Plan a multimodal trip between two coordinates
search_stops
g., "Times Square", "Main St & 5th Ave"). Returns matching stops with IDs, names, coordinates, routes, and relevance scores. Use this when you know the stop name or intersection but not exact coordinates. Search for transit stops by name or address
Example Prompts for TripGo in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with TripGo immediately.
"Plan a trip from Central Station to Opera House using only public transit and walking"
"What buses are departing from Stop 12345 in the next 15 minutes?"
"Show me all train and bus vehicles currently running on Route 480"
Troubleshooting TripGo MCP Server with LlamaIndex
Common issues when connecting TripGo to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTripGo + LlamaIndex FAQ
Common questions about integrating TripGo 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?
Connect TripGo with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect TripGo to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.