How to Use the TransportAPI Alternative MCP in AutoGen

Q: How can AutoGen determine a journey plan with TransportAPI Alternative?

The agents initiate the process by calling planpublictransportjourney. They then use subsequent calls, like checking fares with gettrainfares, to validate and improve the initial suggested route.

Q: What if I need timetable data with TransportAPI Alternative and AutoGen?

Agents can compare schedules. One calls gettrainstationtimetable, and another uses getbusroutetimetable to give the user a complete, debated view of all available timings.

Q: Is there an easy way to find nearby locations for AutoGen?

The MCP Server has getnearbytransportplaces. An agent can call this with GPS data and then pass the results to a second tool like getbusservice to get further details.

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Setup TransportAPI Alternative with AutoGen

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Perplexity

MCP Server: Multi-Agent Routing

Agents can debate complex journeys. Have one agent call `plan_public_transport_journey` and another challenge its findings by calling `get_train_service_details`. The discussion converges on the best route. This process requires multiple tool calls, making it ideal for AutoGen's multi-agent dialogue structure.

Live Departures Negotiation

One agent can check `get_live_bus_departures` while a performance agent checks `get_nearby_transport_places`. They negotiate the best time to leave based on real-time data. This use case proves that the MCP Server supports dynamic, multi-tool decision-making where agents challenge each other's tool inputs and outputs.

Station Discovery Debate

Agents can debate how to find a starting point. One calls `search_transport_places` by name; another uses `get_nearby_bus_stops` with GPS data. They reconcile the two datasets for the user. This ability to cross-reference location data from different MCP tools is what makes AutoGen powerful here.

Setup guide

Set up TransportAPI Alternative MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes TransportAPI Alternative tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="TransportAPI Alternative_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent TransportAPI Alternative data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="TransportAPI Alternative_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent TransportAPI Alternative data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by TransportAPI. 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 TransportAPI Alternative MCP in AutoGen

The agents initiate the process by calling `plan_public_transport_journey`. They then use subsequent calls, like checking fares with `get_train_fares`, to validate and improve the initial suggested route.

Yes. When a user only provides a postcode, an agent can first call `get_transport_by_postcode` using the MCP Server to find local options before planning any specific trip.

Agents can compare schedules. One calls `get_train_station_timetable`, and another uses `get_bus_route_timetable` to give the user a complete, debated view of all available timings.

The MCP Server has `get_nearby_transport_places`. An agent can call this with GPS data and then pass the results to a second tool like `get_bus_service` to get further details.

It primarily handles public transit schedule data, including bus routes, train timetables (`get_bus_route_timetable`), and live departure times. No personal identifying information is stored or passed.

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