How to Use the Transport for London MCP in OpenAI Agents SDK

Q: Does the OpenAI Agents SDK handle multiple transport modes for Transport for London?

Yes. The getjourney tool handles combining tube lines, buses, walking routes, and even cycling directions into one comprehensive plan.

Build production agents that manage Transport for London data flow using OpenAI Agents SDK.

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Connect Transport for London MCP to OpenAI Agents SDK

Create your Vinkius account to connect Transport for London to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Transport for London with OpenAI Agents SDK

Ask AI about this MCP

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Claude

Perplexity

Plan complex journeys across London

You can ask your agent to map out a full trip, regardless of the starting point. It uses `get_journey` to return multiple route options, calculating estimated duration, fare cost, and walking distance between station names or postcodes. The system also handles multi-modal transit planning. This means it finds paths combining tube lines, buses, and even cycling routes in a single request.

Monitor real-time TFL status via MCP Server

The agent checks the live health of the system using `get_line_status` or `get_road_disruptions`. You don't have to check lines individually; just giving it a list of IDs (like 'central,victoria') gets you all the status updates at once. It also pulls detailed disruption reports, telling you exactly what caused the problem and when they predict the area will clear.

Find bikes or bus stops quickly

Need to know where to catch a bus? Use `search_stop` first; it returns IDs for any stop by name. Then, your agent uses that ID with `get_arrivals` to get predicted arrival times and line numbers. For cycling trips, the toolset includes `get_bike_points`, letting you find nearby stations and checking exactly how many docks are free.

Setup guide

Set up Transport for London MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Transport for London tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Transport for London tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Transport for London tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Transport for London Agent",
            instructions="You have access to Transport for London tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Transport for London. 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.

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Common questions about Transport for London MCP in OpenAI Agents SDK

Your agent discovers the MCP tools automatically, so you don't need to write specific code wrappers. You just tell your client what task needs doing (e.g., 'What is the status of the Northern Line?') and the underlying system executes the correct tool.

Absolutely. You can pass station names, addresses, or postcodes to `get_journey`, and the MCP Server calculates the best route options immediately. It's designed for complex, multi-stop trips.

This server handles public transit metadata, specifically including line status updates and predicted arrival times at bus stops. It never touches personal passenger data.

Yes. The `get_journey` tool handles combining tube lines, buses, walking routes, and even cycling directions into one comprehensive plan.

The MCP Server gives you line statuses (Good Service, Minor Delays, etc.) using `get_line_status`, and it also provides current road congestion levels via `get_road_status`.

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