TollGuru MCP Server for LlamaIndex 3 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add TollGuru 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 TollGuru. "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in TollGuru?"
)
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 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.
LlamaIndex agents combine TollGuru tool responses with indexed documents for comprehensive, grounded answers. Connect 3 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.
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 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 TollGuru to LlamaIndex via MCP
Follow these steps to integrate the TollGuru 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 3 tools from TollGuru
Why Use LlamaIndex with the TollGuru MCP Server
LlamaIndex provides unique advantages when paired with TollGuru through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine TollGuru tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain TollGuru tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query TollGuru, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what TollGuru tools were called, what data was returned, and how it influenced the final answer
TollGuru + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the TollGuru MCP Server delivers measurable value.
Hybrid search: combine TollGuru real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query TollGuru 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 TollGuru for fresh data
Analytical workflows: chain TollGuru queries with LlamaIndex's data connectors to build multi-source analytical reports
TollGuru MCP Tools for LlamaIndex (3)
These 3 tools become available when you connect TollGuru to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting TollGuru to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTollGuru + LlamaIndex FAQ
Common questions about integrating TollGuru 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 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 LlamaIndex
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.