How to Use the TfL MCP in Google ADK

Q: How can Google ADK manage complex TfL journey planning?

The agent runs getjourney to get comprehensive trip details. Since you're in the Gemini ecosystem, you can feed these multiple route options directly into BigQuery for further analysis.

Q: What is the scope of TfL line status checks with Google ADK?

The getlinestatus tool covers virtually every mode: tube, bus, tram, overground, and more. This means your agent can check reliability across the entire London transport ecosystem.

Q: Can I use Google ADK to search for TfL points of interest?

Yes. The getplacesearch tool lets you find anything from parks near Westminster to specific hospitals, giving your agent the necessary context before planning a trip.

Q: What data type does this TfL MCP Server touch for place discovery?

It uses getplacesearch and returns detailed information including Place IDs, names, categories, and geographic coordinates.

Q: How is the accuracy of TfL data handled when using Google ADK?

The MCP Server provides real-time inputs for services like getarrivals, giving precise predicted arrival times down to the minute for any given stop point.

Build enterprise agents with Google ADK. Deep TfL data integration for BigQuery workflows.

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Connect TfL MCP to Google ADK

Create your Vinkius account to connect TfL to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup TfL with Google ADK

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Plan multi-modal journeys using MCP Server

The `get_journey` tool provides complete trip planning, combining every mode from tube to river to cycle. It returns detailed instructions and total duration for every option. Your agent can compare these complex routes, making it ideal for building enterprise systems that need multiple transport options.

Check service reliability via MCP Server

The `get_line_status` tool queries all TfL lines and modes instantly. You get the severity level—whether it's 'Good Service' or 'Part Suspended.' This data is crucial for large-scale planning, allowing your agent to flag systemic issues across multiple London assets.

Find all bike docking stations using MCP Server

Use `get_bike_points` to list thousands of Santander Cycles docks. This tool returns the ID, common name, coordinates, and capacity for every station in central London. It’s perfect for mapping out an entire city's bike-sharing network within a large cloud data model.

Setup guide

Set up TfL 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 TfL 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="TfL_agent",
    model="gemini-2.0-flash",
    instruction="You have access to TfL tools via MCP.",
    tools=mcp_tools,
)

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Common questions about TfL MCP in Google ADK

The agent runs `get_journey` to get comprehensive trip details. Since you're in the Gemini ecosystem, you can feed these multiple route options directly into BigQuery for further analysis.

The `get_line_status` tool covers virtually every mode: tube, bus, tram, overground, and more. This means your agent can check reliability across the entire London transport ecosystem.

Yes. The `get_place_search` tool lets you find anything from parks near Westminster to specific hospitals, giving your agent the necessary context before planning a trip.

It uses `get_place_search` and returns detailed information including Place IDs, names, categories, and geographic coordinates.

The MCP Server provides real-time inputs for services like `get_arrivals`, giving precise predicted arrival times down to the minute for any given stop point.

Use it with your favorite AI tools

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

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