Can my AI check when the next bus is arriving at a specific UK bus stop?

Yes! First use `search_stops` to find the bus stop by name or location (e.g., "Oxford Street" or "Piccadilly Circus"). This returns the Naptan stop ID. Then use `get_bus_departures` with that stop ID to see all upcoming departures with expected arrival times, line numbers, destinations, and any delay information. You can also use `get_bus_arrivals` to monitor incoming services. The API provides real-time predictions based on live vehicle tracking across Great Britain.

How do I plan a complete journey from my hotel to a UK attraction using public transport?

Use the `get_journey_plan` tool with your hotel address or postcode as the origin and the attraction name or postcode as the destination. The TransportAPI journey planner will return complete multimodal itineraries combining buses, trains, trams, underground (tube), walking, and cycling with departure times, arrival times, total duration, number of changes, detailed legs with line names and operators, walking distances, and real-time disruption alerts. You can also specify a desired departure or

Can I check if there are any disruptions or engineering works affecting UK rail services?

Absolutely! Use `get_updates` to fetch current service alerts and disruption notices across the UK transport network. You can filter by mode ("rail" for trains, "bus" for buses) to get targeted alerts. The results include affected lines or stations, disruption descriptions, severity levels, expected duration, and alternative route recommendations. For station-specific information, use `get_rail_departures` or `get_rail_arrivals` which include cancellation and delay indicators for individual serv

TransportAPI MCP Server for OpenAI Agents SDK 12 tools — connect in under 2 minutes

Name: TransportAPI
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 12 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect TransportAPI through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="TransportAPI Assistant",
            instructions=(
                "You help users interact with TransportAPI. "
                "You have access to 12 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from TransportAPI"
        )
        print(result.final_output)

asyncio.run(main())

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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 OpenAI Agents SDK auto-discovers all 12 tools from TransportAPI through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries TransportAPI, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

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 OpenAI Agents 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 OpenAI Agents SDK via MCP

Follow these steps to integrate the TransportAPI MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 12 tools from TransportAPI

Why Use OpenAI Agents SDK with the TransportAPI MCP Server

OpenAI Agents SDK provides unique advantages when paired with TransportAPI through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

TransportAPI + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the TransportAPI MCP Server delivers measurable value.

Automated workflows: build agents that query TransportAPI, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries TransportAPI, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through TransportAPI tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query TransportAPI to resolve tickets, look up records, and update statuses without human intervention

TransportAPI MCP Tools for OpenAI Agents SDK (12)

These 12 tools become available when you connect TransportAPI to OpenAI Agents SDK via MCP:

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

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

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

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

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

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

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

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

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

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

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

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 OpenAI Agents SDK

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

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

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

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

Troubleshooting TransportAPI MCP Server with OpenAI Agents SDK

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

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

TransportAPI + OpenAI Agents SDK FAQ

Common questions about integrating TransportAPI MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.