How to Use the TransportAPI MCP in Google ADK

Q: How does TransportAPI help with complex routing in Google ADK?

The agent uses the getjourneyplan tool to map out multimodal trips. It handles combining bus, rail, tube, and walking legs into one cohesive itinerary for your Gemini models.

Q: Can I check departures using TransportAPI with Google ADK?

Yes. You can call getraildepartures or getbusdepartures. Both tools return real-time ETDs, destinations, and platform information for specific UK stations or stops.

Q: Does TransportAPI handle service alerts for Google ADK?

It does. The getupdates tool provides a unified view of disruptions affecting bus, rail, tram, and underground services across Great Britain. This ensures your agent's advice is always timely.

Q: How do I search for stops using TransportAPI with Google ADK?

You use searchstops to find matching bus stops by name or landmark. The results provide Naptan stop IDs, served lines, and locality details, which are necessary inputs for other planning tools.

Real-time UK public transit data for your Google ADK enterprise agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect TransportAPI MCP to Google ADK

Create your Vinkius account to connect TransportAPI to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup TransportAPI with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Model comprehensive journey planning.

`get_journey_plan` supports multimodal trips across the entire UK network. It gives you a full itinerary, detailing departure and arrival times from bus to rail to tram. The result includes total duration, change counts, and mode details for every leg. Since your agent works with BigQuery data, you can easily pipe this structured trip data into your existing datasets for deeper analysis of travel patterns.

Get detailed station metadata.

`get_station_info` gives you deep operational details about UK rail stations. You get the name, address, staff hours, whether they have ticket machines, and accessibility status (e.g., step-free access). This makes your agent reliable for planning physical trips because it validates facility availability before suggesting a location.

Track departures from any UK stop.

`get_bus_departures` provides real-time departure listings, covering all services across Great Britain. You get line numbers, destinations, and the expected wait time for every service at a given stop. When building enterprise monitoring tools, having access to `get_rail_departures` alongside this gives you total coverage of both bus and train departures.

Setup guide

Set up TransportAPI MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with TransportAPI tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="TransportAPI_agent",
    model="gemini-2.0-flash",
    instruction="You have access to TransportAPI tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by TransportAPI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect TransportAPI now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about TransportAPI MCP in Google ADK

The agent uses the `get_journey_plan` tool to map out multimodal trips. It handles combining bus, rail, tube, and walking legs into one cohesive itinerary for your Gemini models.

Yes. You can call `get_rail_departures` or `get_bus_departures`. Both tools return real-time ETDs, destinations, and platform information for specific UK stations or stops.

It does. The `get_updates` tool provides a unified view of disruptions affecting bus, rail, tram, and underground services across Great Britain. This ensures your agent's advice is always timely.

This MCP Server touches location coordinates (latitude/longitude), service disruption notices, train operating companies, bus stop IDs, and scheduled time patterns. This rich data set powers your enterprise agents.

You use `search_stops` to find matching bus stops by name or landmark. The results provide Naptan stop IDs, served lines, and locality details, which are necessary inputs for other planning tools.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript