Can my AI calculate the total toll costs for a road trip from New York to Boston?

Yes! Use the `calculate_toll_route` tool with origin="New York, NY" and destination="Boston, MA". You can specify your vehicle type (2AxlesAuto for regular cars, 2AxlesEV for electric vehicles, or truck types like 5AxlesTruck for commercial vehicles). The API returns detailed toll plaza names, tag and cash costs for each plaza, total toll cost, fuel cost estimate, and optional driver cost. You can also request costs in different currencies and compare payment methods (tag vs cash vs prepaid card

How do I get toll costs for a route I already have from Google Maps?

Use the `calculate_toll_from_polyline` tool with the encoded polyline from Google Maps. Set source="google" and paste the polyline string. This calculates tolls for your exact route without re-routing. You can also specify vehicle type and currency. This is perfect when you have an existing route and need toll costs for trip budgeting or fleet expense tracking.

Can I optimize a multi-stop delivery route to minimize toll costs?

Absolutely! Use the `calculate_toll_multi_stop` tool with your origin, destination, and comma-separated waypoints. Set optimize_waypoints="true" to let TollGuru find the most cost-effective waypoint order. The API returns the optimized route with total toll costs, fuel costs, and detailed plaza-by-plaza breakdown. This is essential for logistics planning, delivery route optimization, and fleet cost management.

TollGuru MCP Server for Google ADK 3 tools — connect in under 2 minutes

Name: TollGuru
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 3 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add TollGuru as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="tollguru_agent",
    instruction=(
        "You help users interact with TollGuru "
        "using 3 available tools."
    ),
    tools=[mcp_tools],
)

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* 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.

Google ADK natively supports TollGuru as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 3 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

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 Google ADK 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 Google ADK via MCP

Follow these steps to integrate the TollGuru MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 3 tools from TollGuru via MCP

Why Use Google ADK with the TollGuru MCP Server

Google ADK provides unique advantages when paired with TollGuru through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with TollGuru

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine TollGuru tools with BigQuery, Vertex AI, and Cloud Functions

TollGuru + Google ADK Use Cases

Practical scenarios where Google ADK combined with the TollGuru MCP Server delivers measurable value.

Enterprise data agents: ADK agents query TollGuru and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine TollGuru tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query TollGuru regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including TollGuru

TollGuru MCP Tools for Google ADK (3)

These 3 tools become available when you connect TollGuru to Google ADK 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 Google ADK

Ready-to-use prompts you can give your Google ADK 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 Google ADK

Common issues when connecting TollGuru to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

TollGuru + Google ADK FAQ

Common questions about integrating TollGuru MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.