TripGo MCP Server for LangChain 9 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect TripGo through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"tripgo": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using TripGo, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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:
LangChain's ecosystem of 500+ components combines seamlessly with TripGo through native MCP adapters. Connect 9 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
- 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 LangChain 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 LangChain via MCP
Follow these steps to integrate the TripGo MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 9 tools from TripGo via MCP
Why Use LangChain with the TripGo MCP Server
LangChain provides unique advantages when paired with TripGo through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine TripGo MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across TripGo queries for multi-turn workflows
TripGo + LangChain Use Cases
Practical scenarios where LangChain combined with the TripGo MCP Server delivers measurable value.
RAG with live data: combine TripGo tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query TripGo, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain TripGo tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every TripGo tool call, measure latency, and optimize your agent's performance
TripGo MCP Tools for LangChain (9)
These 9 tools become available when you connect TripGo to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting TripGo to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersTripGo + LangChain FAQ
Common questions about integrating TripGo MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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 LangChain
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.
