TomTom Parking Availability 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 TomTom Parking Availability as an MCP tool provider through the 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 TomTom Parking Availability. "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in TomTom Parking Availability?"
)
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 TomTom Parking Availability MCP Server
Empower your AI agent to orchestrate your entire urban mobility and parking auditing workflow with TomTom Parking Availability, the comprehensive source for real-time parking data. By connecting the TomTom API to your agent, you transform complex location searches into a natural conversation. Your agent can instantly search for parking facilities, audit address metadata, and retrieve coordinate details without you ever touching a navigation app. Whether you are conducting logistics research or managing regional fleet constraints, your agent acts as a real-time mobility consultant, ensuring your data is always precise and localized.
LlamaIndex agents combine TomTom Parking Availability tool responses with indexed documents for comprehensive, grounded answers. Connect 3 tools through the 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
- Parking Auditing — Search for thousands of parking spots near a specific location and retrieve detailed metadata, including facility names and addresses.
- Location Oversight — Audit the exact geographic coordinates for specific parking facilities to understand local distribution instantly.
- Availability Discovery — Query detailed POI information for specific parking IDs to assist in deep-dive urban planning.
- Mobility Intelligence — Retrieve high-resolution location details to assist in regional logistics and fleet management.
- Operational Monitoring — Check API status to ensure your mobility research workflow is always operational.
The TomTom Parking Availability 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 TomTom Parking Availability to LlamaIndex via MCP
Follow these steps to integrate the TomTom Parking Availability 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 TomTom Parking Availability
Why Use LlamaIndex with the TomTom Parking Availability MCP Server
LlamaIndex provides unique advantages when paired with TomTom Parking Availability through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine TomTom Parking Availability tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain TomTom Parking Availability tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query TomTom Parking Availability, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what TomTom Parking Availability tools were called, what data was returned, and how it influenced the final answer
TomTom Parking Availability + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the TomTom Parking Availability MCP Server delivers measurable value.
Hybrid search: combine TomTom Parking Availability real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query TomTom Parking Availability 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 TomTom Parking Availability for fresh data
Analytical workflows: chain TomTom Parking Availability queries with LlamaIndex's data connectors to build multi-source analytical reports
TomTom Parking Availability MCP Tools for LlamaIndex (3)
These 3 tools become available when you connect TomTom Parking Availability to LlamaIndex via MCP:
check_api_status
Check if the TomTom Parking service is operational
get_parking_details
Get full details and availability metadata for a specific parking ID
search_parking_spots
Search for parking spots near a specific location
Example Prompts for TomTom Parking Availability in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with TomTom Parking Availability immediately.
"Search for parking spots in 'San Francisco' using TomTom."
"What is the availability for parking ID '12345'?"
"Find parking near latitude 37.7749 and longitude -122.4194."
Troubleshooting TomTom Parking Availability MCP Server with LlamaIndex
Common issues when connecting TomTom Parking Availability to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTomTom Parking Availability + LlamaIndex FAQ
Common questions about integrating TomTom Parking Availability 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 TomTom Parking Availability 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 Parking Availability to LlamaIndex
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.