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TransportAPI MCP Server for Vercel AI SDK 12 tools — connect in under 2 minutes

Built by Vinkius GDPR 12 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect TransportAPI through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

Vinkius supports streamable HTTP and SSE.

typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

async function main() {
  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      // Your Vinkius token. get it at cloud.vinkius.com
      url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    },
  });

  try {
    const tools = await mcpClient.tools();
    const { text } = await generateText({
      model: openai("gpt-4o"),
      tools,
      prompt: "Using TransportAPI, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
TransportAPI
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* 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 TransportAPI MCP Server

Connect your TransportAPI UK public transport data platform to any AI agent and take full control of real-time bus and rail tracking, multimodal journey planning, and service disruption monitoring across Great Britain through natural conversation.

The Vercel AI SDK gives every TransportAPI tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 12 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.

What you can do

  • Real-Time Bus Tracking — Check upcoming departures and arrivals at any UK bus stop with ETAs and delay indicators
  • Rail Services — Monitor train arrivals, departures, and services at any UK rail station
  • Journey Planning — Plan door-to-door multimodal trips combining bus, rail, tram, underground, walking, and cycling
  • Stop Discovery — Search UK bus stops by name, address, or landmark with Naptan identifiers
  • Route Analysis — Get train route information between any two UK rail stations with calling points
  • Service Updates — Check real-time disruption alerts and operational notices across UK transport networks
  • Bus Timetables — Access complete timetables for any UK bus line with weekday/weekend patterns
  • Station Information — Get detailed UK rail station data including facilities, accessibility, and managing TOCs
  • Stop Details — Retrieve comprehensive bus stop information with served lines and accessibility features

The TransportAPI MCP Server exposes 12 tools through the Vinkius. Connect it to Vercel AI SDK 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 TransportAPI to Vercel AI SDK via MCP

Follow these steps to integrate the TransportAPI MCP Server with Vercel AI SDK.

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the script

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

The SDK discovers 12 tools from TransportAPI and passes them to the LLM

Why Use Vercel AI SDK with the TransportAPI MCP Server

Vercel AI SDK provides unique advantages when paired with TransportAPI through the Model Context Protocol.

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same TransportAPI integration everywhere

03

Built-in streaming UI primitives let you display TransportAPI tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

TransportAPI + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the TransportAPI MCP Server delivers measurable value.

01

AI-powered web apps: build dashboards that query TransportAPI in real-time and stream results to the UI with zero loading states

02

API backends: create serverless endpoints that orchestrate TransportAPI tools and return structured JSON responses to any frontend

03

Chatbots with tool use: embed TransportAPI capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with TransportAPI through natural language queries

TransportAPI MCP Tools for Vercel AI SDK (12)

These 12 tools become available when you connect TransportAPI to Vercel AI SDK via MCP:

01

get_bus_arrivals

Returns list of arriving services with line names and numbers, origins, scheduled and real-time arrival times (ETA), expected wait times, direction, operator details, and any delay indicators. Essential for passenger pickup coordination, arrival monitoring, and real-time arrival boards. AI agents use this when users ask "when is the next bus arriving at this stop", "show incoming buses at stop X", or need to track arriving bus services for passenger coordination. Get real-time bus arrivals at a specific UK stop

02

get_bus_departures

Returns list of departing services with line names and numbers, destinations, scheduled and real-time departure times (ETD), expected wait times, direction, operator details, and any service disruption notices. Covers all bus services across Great Britain including London Buses, Transport for Greater Manchester, West Midlands, and regional operators. Essential for passenger information displays, departure boards, journey planning, and real-time transit monitoring. AI agents should reference this when users ask "when is the next bus from this stop", "show departures from stop ID X", or need to monitor upcoming bus services at a known UK bus stop. Get real-time bus departures from a specific stop in the UK

03

get_journey_plan

Supports multimodal trips combining bus, rail, tram, underground (tube), walking, and cycling. Returns complete itinerary with departure and arrival times, total duration, number of changes, legs with mode details (line name, operator, vehicle type), intermediate stops/stations, walking distances, and real-time disruption information. Essential for travel planning, multimodal journey optimization, passenger information systems, and UK-wide mobility applications. AI agents should use this when users ask "how do I get from London Victoria to Heathrow Airport", "plan a journey from Manchester Piccadilly to Old Trafford", or need door-to-door trip planning across UK public transport. Plan a multimodal journey between two UK locations

04

get_rail_arrivals

Returns list of arriving services with train operating companies, origins, scheduled and real-time arrival times (ETA), platforms, expected delays, cancellation status, and service type information. Covers all National Rail services. Essential for passenger pickup coordination, arrival monitoring, station management, and real-time arrival boards. AI agents use this when users ask "what trains are arriving at Kings Cross", "show incoming trains at Manchester Piccadilly", or need to track arriving rail services. Get real-time train arrivals at a specific UK rail station

05

get_rail_departures

Returns list of departing services with train operating companies, destinations, scheduled and real-time departure times (ETD), platforms, expected delays, cancellation status, calling points, and service type (express, local, sleeper). Covers all National Rail services across Great Britain. Essential for departure boards, journey planning, station operations, and passenger information. AI agents should use this when users ask "what trains are leaving Paddington", "show departures from Birmingham New Street", or need comprehensive departure listings for a UK rail station. Get real-time train departures from a specific UK rail station

06

get_rail_route

Returns available services, journey duration, number of changes, calling points, train operating companies, typical frequency, and first/last service times. Essential for rail journey planning, route comparison, travel itinerary preparation, and understanding rail connectivity. AI agents should reference this when users ask "what is the train route from London to Manchester", "show rail connections between Edinburgh and Glasgow", or need to understand rail service options between two UK stations. Get train route information between two UK rail stations

07

get_rail_services

Returns services with train operating companies (TOCs), destinations, origins, scheduled times, platforms, service types (express, local, sleeper), and any disruption information. Covers National Rail services across Great Britain. Essential for station information displays, service monitoring, rail journey planning, and operational awareness. AI agents should reference this when users ask "what services call at Euston", "show all trains at Edinburgh Waverley", or need comprehensive service listings for a UK rail station. Get all train services calling at a specific UK rail station

08

get_station_info

Returns station name, location (address, latitude, longitude), facilities (ticket office, ticket machines, waiting room, car park, cycle storage, WiFi, step-free access), staffing hours, managing train operating company, annual entry/exit statistics, and accessibility information. Essential for station planning, accessibility assessment, facility verification, and passenger information. AI agents should use this when users ask "tell me about Clapham Junction station", "does Euston have step-free access", or need detailed station metadata for UK rail journey planning. Get detailed information about a specific UK rail station

09

get_stop_info

Returns stop name, location (latitude, longitude, address, locality, landmark), common services, served lines, stop type (bus stop, bus station, coach station), accessibility features (wheelchair access, sheltered, seating), and operator information. Essential for stop identification, accessibility planning, transit network analysis, and passenger information. AI agents should use this when users ask "tell me about this bus stop", "what lines serve stop X", or need detailed stop metadata to contextualize transit queries. Get detailed information about a specific UK bus stop

10

get_timetable

Returns all scheduled services with departure times from origin through to terminus, stops served in sequence, journey duration variations by time of day, weekday/weekend/holiday service patterns, operator information, and any planned service changes. Essential for comprehensive schedule analysis, journey planning at specific times, service pattern research, and understanding bus frequency throughout the day. AI agents use this when users ask "show me the full timetable for bus route 73", "what times does the X59 run on Sundays", or need complete schedule data for a UK bus service. Get full timetable for a specific UK bus line

11

get_updates

Returns active alerts with affected lines, services, or operators, disruption descriptions, severity levels, expected duration, alternative route recommendations, and timestamps. Covers bus, rail, tram, and underground services across Great Britain. Essential for disruption awareness, passenger communication, journey reliability monitoring, and travel planning during service changes. AI agents should reference this when users ask "are there any disruptions on the Northern Line", "is there engineering work on Great Western Railway", or need to check service reliability before planning UK journeys. Get real-time service updates and disruption alerts for UK transport

12

search_stops

Returns matching stops with Naptan stop IDs, names, locations (latitude, longitude), served lines, localities, and stop types. Essential for stop discovery, journey planning interfaces, transit stop identification, and building location-based transit features. AI agents should use this when users ask "find the bus stop near Oxford Street", "search for stops called Piccadilly", or need to identify Naptan stop IDs for use in departure/arrival queries. Search for UK bus stops by name, location, or landmark

Example Prompts for TransportAPI in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with TransportAPI immediately.

01

"Show me all bus departures from Oxford Circus in the next 30 minutes."

02

"What trains are departing from London Paddington to Bristol in the next 2 hours?"

03

"Plan a journey from Manchester Airport to the city centre using public transport."

Troubleshooting TransportAPI MCP Server with Vercel AI SDK

Common issues when connecting TransportAPI to Vercel AI SDK through the Vinkius, and how to resolve them.

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

TransportAPI + Vercel AI SDK FAQ

Common questions about integrating TransportAPI MCP Server with Vercel AI SDK.

01

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
02

Can I use MCP tools in Edge Functions?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
03

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.

Connect TransportAPI to Vercel AI SDK

Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.