How to Use the Transport for London MCP in Vercel AI SDK

Q: How can I check bus arrivals using Transport for London and Vercel AI SDK?

Call searchstop first to get the stop ID. Then, pass that ID into getarrivals. Your agent uses this two-step process to pull live data that streams right into your frontend UI.

Q: Does Vercel AI SDK handle Transport for London journey planning?

Yes. The getjourney tool handles trip planning, taking inputs like addresses or postcodes and returning a full set of options including walking distance and fare estimates.

Q: Can I check road disruptions with Transport for London using Vercel AI SDK?

You absolutely can. The getroaddisruptions tool pulls disruption details, including severity and estimated clearance times, so you don't have to worry about traffic stopping your app.

Q: How do I get detailed info for a specific bus stop or station?

Use the getstopdetails tool. This is critical because it gives you the exact IDs needed before running other queries like checking arrivals.

Build real-time London transit experiences with Vercel AI SDK's streaming MCP integration.

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Connect Transport for London MCP to Vercel AI SDK

Create your Vinkius account to connect Transport for London to Vercel AI 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 Vercel AI SDK

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Live Bus Arrival Predictions

The `get_arrivals` tool gives you predicted arrival times, destination, line number, and vehicle ID. You pass the stop point ID, which you first grab using `search_stop`, so your frontend shows data updating live as buses approach. Because Vercel AI SDK streams results, users see the bus timing numbers appear instantly—no loading spinner needed. It's perfect for a responsive UI that feels snappy.

Multi-Modal Journey Planning

Don't make users guess how to get around. The `get_journey` tool plans the route between two points, returning estimated duration, fare cost, and step-by-step directions for walking or transit. This data streams directly into your React component, letting you build a flawless user experience. You can even integrate bike availability using `get_bike_points` right next to the journey map.

Real-Time Service Status Monitoring

`get_line_status` checks if specific tube lines have Good Service, Minor Delays, or are Suspended. You can check all lines at once or target just 'central' and 'victoria'. This streamable data lets your agent instantly update a status bar on your page when delays hit. It makes the MCP Server crucial for building reliable passenger tools.

Setup guide

Set up Transport for London MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Transport for London tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Transport for London transactions",
});

console.log(text);
await mcpClient.close();

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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 Vercel AI SDK

Call `search_stop` first to get the stop ID. Then, pass that ID into `get_arrivals`. Your agent uses this two-step process to pull live data that streams right into your frontend UI.

Yes. The `get_journey` tool handles trip planning, taking inputs like addresses or postcodes and returning a full set of options including walking distance and fare estimates.

The server touches live transport status data, specifically line statuses (Good Service, Delays) and bus arrival predictions. This is all real-time operational data.

You absolutely can. The `get_road_disruptions` tool pulls disruption details, including severity and estimated clearance times, so you don't have to worry about traffic stopping your app.

Use the `get_stop_details` tool. This is critical because it gives you the exact IDs needed before running other queries like checking arrivals.

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