TomTom MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect TomTom 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({
"tomtom": {
"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 TomTom, 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 TomTom MCP Server
Connect your TomTom API account directly to any AI agent to unlock enterprise-grade geospatial and logistical capabilities native to your platform. Convert complex addresses instantly, evaluate driving routes based on exact origin and destination coordinates, and visualize live traffic blocks directly through chat queries.
LangChain's ecosystem of 500+ components combines seamlessly with TomTom through native MCP adapters. Connect 10 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.
What you can do
- Precision Geocoding — Process any physical address string into absolute geographic latitude/longitude coordinates using fuzzy logic or structured fields, as well as reversing coordinates back to plain street names
- Route Computation — Calculate the exact travel time, polyline geometry, and distance for a trip between two precise coordinates
- Real-Time Traffic — Map traffic incidents (accidents, constructions, jams) constrained within a bounding box, or survey the traffic flow speed of a particular avenue segment
- Poi Discovery — Find global Points of Interest based on categories (e.g., hospitals, fuel) and retrieve rich contact metadata or opening hours for specific locations
- Travel Boundaries — Calculate reachable ranges (polygonal limits) to understand exactly how far your fleet or agents can travel within a set time budget
The TomTom MCP Server exposes 10 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 TomTom to LangChain via MCP
Follow these steps to integrate the TomTom 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 10 tools from TomTom via MCP
Why Use LangChain with the TomTom MCP Server
LangChain provides unique advantages when paired with TomTom through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine TomTom 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 TomTom queries for multi-turn workflows
TomTom + LangChain Use Cases
Practical scenarios where LangChain combined with the TomTom MCP Server delivers measurable value.
RAG with live data: combine TomTom tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query TomTom, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain TomTom tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every TomTom tool call, measure latency, and optimize your agent's performance
TomTom MCP Tools for LangChain (10)
These 10 tools become available when you connect TomTom to LangChain via MCP:
autocomplete_place_search
Provide a partial string and optional bias coordinates. Provides predictive location suggestions based on partial input
calculate_reachable_range
Provide center coordinates and a time budget in seconds. Calculates an area reachable within a specific time or distance budget
calculate_route
Returns the route polyline and a summary. Calculates a route and travel time between two points
fuzzy_geocoding
Converts a physical address string into geographic coordinates using fuzzy matching
get_poi_details
Retrieves rich metadata for a specific point of interest ID
get_traffic_flow_segment
Provide center coordinates. Retrieves the traffic flow speed and quality for a specific road segment
get_traffic_incidents
Provide min/max lat/lon coordinates. Retrieves real-time traffic incident details within a bounding box
reverse_geocoding
Converts geographic coordinates into a physical address
search_poi_by_category
Provide a category name and a center coordinate. Searches for points of interest (POIs) near a location by category (e.g., gas stations, hospitals)
structured_geocoding
Provide parameters like countryCode and postalCode. Performs geocoding using explicit address components (e.g., street, city, zip)
Example Prompts for TomTom in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with TomTom immediately.
"Convert these coordinates into an address: Lat 40.7128, Lon -74.0060."
"Check for any traffic incidents on the 101 freeway bounded roughly by these dimensions."
Troubleshooting TomTom MCP Server with LangChain
Common issues when connecting TomTom to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersTomTom + LangChain FAQ
Common questions about integrating TomTom 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 TomTom 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 TomTom to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.