TollGuru MCP Server for LangChain 3 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect TollGuru 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({
"tollguru": {
"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 TollGuru, 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 TollGuru MCP Server
Connect your TollGuru toll calculation API to any AI agent and take full control of trip cost estimation, toll plaza tracking, route optimization, and fleet expense management across 50+ countries through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with TollGuru through native MCP adapters. Connect 3 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
- Toll Calculation — Calculate toll costs for any route with detailed plaza-by-plaza breakdown including tag and cash prices
- Fuel Cost Estimation — Get fuel cost estimates based on vehicle efficiency and current fuel prices along the route
- Driver Cost Analysis — Calculate driver costs based on hourly wage or time value for complete trip budgeting
- Multi-Stop Routes — Calculate tolls for routes with multiple waypoints and optimize waypoint order to minimize tolls
- Route Optimization — Find the most cost-effective route between origin and destination with toll-aware routing
- Polyline Toll Calculation — Calculate tolls for existing routes from Google Maps, Here Maps, or Mapbox polylines
- Vehicle-Specific Pricing — Get accurate toll costs for any vehicle type from 2-axle cars to 9-axle commercial trucks
- Multi-Currency Support — View costs in USD, CAD, MXN, EUR, GBP, INR, AUD, and 12+ other currencies
- Payment Method Breakdown — Compare toll costs by payment method (tag, cash, prepaid card, license plate)
- Global Coverage — Calculate tolls across US, Canada, Mexico, Europe, Australia, India, and 50+ countries
The TollGuru MCP Server exposes 3 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 TollGuru to LangChain via MCP
Follow these steps to integrate the TollGuru 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 3 tools from TollGuru via MCP
Why Use LangChain with the TollGuru MCP Server
LangChain provides unique advantages when paired with TollGuru through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine TollGuru 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 TollGuru queries for multi-turn workflows
TollGuru + LangChain Use Cases
Practical scenarios where LangChain combined with the TollGuru MCP Server delivers measurable value.
RAG with live data: combine TollGuru tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query TollGuru, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain TollGuru tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every TollGuru tool call, measure latency, and optimize your agent's performance
TollGuru MCP Tools for LangChain (3)
These 3 tools become available when you connect TollGuru to LangChain via MCP:
calculate_toll_from_polyline
This is useful when you already have a route from a mapping service and need toll calculations without re-routing. Returns the same detailed toll, fuel, and cost information as the route calculation. Supports all vehicle types, currencies, and payment methods. Essential for integrating with existing mapping applications, post-trip toll reconciliation, and GPS track-based toll analysis. AI agents should use this when users have an existing route polyline from Google Maps, Here Maps, or another service and need toll costs for that specific route. Calculate tolls for a route defined by an encoded polyline from any mapping service
calculate_toll_multi_stop
Returns detailed breakdown of tolls at each plaza along the complete route, fuel costs, and optional driver costs. Supports waypoint optimization to minimize total toll costs. Essential for delivery route planning, multi-stop trip budgeting, and logistics optimization. AI agents should use this when users need toll calculations for routes with multiple stops, such as "calculate tolls from Chicago to Detroit with stops in Toledo and Ann Arbor" or "what are the toll costs for my delivery route with 5 waypoints". Calculate tolls for a multi-stop route with multiple waypoints
calculate_toll_route
Returns detailed toll plaza information including plaza names, tag and cash costs, payment methods accepted, and route optimization suggestions. Also calculates fuel costs based on vehicle efficiency and current fuel prices, and optional driver costs based on time value. Supports all vehicle types including 2-axle cars, EVs, motorcycles, and commercial trucks (2-9+ axles). You can request route optimization to minimize toll costs, specify currency output (USD, CAD, MXN, EUR, GBP, INR, AUD, etc.), and choose mapping service (Here Maps, Google Maps, or TollGuru internal). Essential for fleet management, trip cost estimation, route planning, toll reconciliation, and travel budgeting. AI agents should use this when users ask "what are the tolls from New York to Boston", "calculate toll costs for my truck from LA to San Francisco", or need comprehensive trip cost breakdowns including tolls, fuel, and driver time. Calculate tolls and total trip costs for a route with origin, destination, and optional waypoints
Example Prompts for TollGuru in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with TollGuru immediately.
"Calculate toll costs for a car trip from San Francisco to Los Angeles."
"What are the toll costs for a 5-axle truck from Chicago to Detroit?"
"Optimize a delivery route with stops in Philadelphia, Baltimore, and Washington DC starting from New York."
Troubleshooting TollGuru MCP Server with LangChain
Common issues when connecting TollGuru to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersTollGuru + LangChain FAQ
Common questions about integrating TollGuru 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 TollGuru 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 TollGuru to LangChain
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.