How to Use the TransportAPI MCP in AutoGen

Q: How does AutoGen use TransportAPI for journey planning?

The agents can be set up to debate the best route using getjourneyplan. One agent might suggest rail, while another challenges it by citing a better bus connection found via the MCP Server.

Q: Can I use TransportAPI with AutoGen to check for delays?

Yes. Agents can run getupdates to pull all service disruptions across the UK transport network, and then debate which disruption most impacts the user's desired route.

Q: Does TransportAPI support querying multiple services with AutoGen?

You can use getrailservices or getbusdepartures. Agents can call these tools to pull comprehensive listings for a station, allowing them to compare all available options before advising the user.

Systematize complex decision making with AutoGen: Multi-agent reasoning over UK transport data.

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Connect TransportAPI MCP to AutoGen

Create your Vinkius account to connect TransportAPI to AutoGen 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 TransportAPI with AutoGen

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Perplexity

Resolve complex travel requirements

The `get_journey_plan` tool is key here. You set up agents that must negotiate a journey—one agent plans the rail portion, another handles the bus connection, and a third calculates walking time. The system converges on one optimal path. Agents use this tool to solve end-to-end mobility problems where multiple data sources are needed.

Coordinate real-time station arrivals

If an agent needs to know when a specific train arrives, it calls `get_rail_arrivals`. Another agent can then use that ETA to calculate the best time for a connecting bus using `get_bus_departures`. This simulates human coordination—agents debate timing and resource availability before proposing a final action.

Audit station facilities and services

Need to know if a station is suitable for bikes? An agent can use `get_station_info` to check for cycle storage. Another agent might cross-reference this with `get_stop_info` to confirm the local bus accessibility. This forces consensus on complex, multi-faceted operational criteria.

Setup guide

Set up TransportAPI 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 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_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent TransportAPI 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_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

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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 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 MCP in AutoGen

The agents can be set up to debate the best route using `get_journey_plan`. One agent might suggest rail, while another challenges it by citing a better bus connection found via the MCP Server.

It delivers structured service listings. This includes operational details like calling points, train operating companies (TOCs), and disruption notices that agents must weigh against each other's proposals.

Yes. Agents can run `get_updates` to pull all service disruptions across the UK transport network, and then debate which disruption most impacts the user's desired route.

You can use `get_rail_services` or `get_bus_departures`. Agents can call these tools to pull comprehensive listings for a station, allowing them to compare all available options before advising the user.

This server handles public transit metadata. It touches non-personal service information, specifically line names and bus/train numbers (service identifiers).

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