How to Use the EMT Madrid (Open Data) MCP in AutoGen

Q: How do I register the EMT Madrid (Open Data) MCP Server in AutoGen?

Use the mcpservertools adapter from the autogen-ext library. Pass your Vinkius server URL to the assistant agent constructor to expose MCP Server tools instantly.

Q: How do agents resolve conflicting routing data?

You can program a critic agent to compare outputs from planbusroute and listbicimadstations to decide if a bus or a bike is the safer bet during rush hour.

Let autonomous AutoGen agents debate routes and coordinate Madrid transit plans using real-time data.

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Connect EMT Madrid (Open Data) MCP to AutoGen

Create your Vinkius account to connect EMT Madrid (Open Data) 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 EMT Madrid (Open Data) with AutoGen

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Coordinate transit plans via multi-agent debate

AutoGen lets you set up multiple agents that discuss and verify travel options. One agent can query `plan_bus_route` to find the fastest path, while a second agent checks `list_bicimad_stations` to see if biking is a viable alternative. They debate the pros and cons of each route before presenting the final decision. This collaborative process ensures your users get the most practical and reliable travel plan.

Track bus arrivals with autonomous supervisors

You can build a supervisor agent that monitors trip progress. The supervisor agent queries `get_bus_arrivals` at set intervals and alerts a passenger agent if a connection is going to be missed. This setup operates without constant human oversight. The agents manage the state, handle the `login` process, and update the route dynamically as traffic conditions change.

Parse transit schemas automatically

AutoGen handles the translation of complex API payloads behind the scenes using this MCP Server. The adapter automatically maps the schemas for tools like `plan_bus_route` so your agents can call them without custom parsing code. This allows you to focus on agent behavior rather than writing glue code. Your agents immediately understand how to format queries and interpret the results.

Setup guide

Set up EMT Madrid (Open Data) 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 EMT Madrid (Open Data) 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="EMT Madrid (Open Data)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent EMT Madrid (Open Data) data")
print(result.messages[-1].content)

Get your connection token →

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="EMT Madrid (Open Data)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent EMT Madrid (Open Data) 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 EMT Madrid. 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 EMT Madrid (Open Data) MCP in AutoGen

Use the `mcp_server_tools` adapter from the `autogen-ext` library. Pass your Vinkius server URL to the assistant agent constructor to expose MCP Server tools instantly.

Yes. You can share the session context across your agent group so they all use the token generated by `login` without authenticating individually.

Yes. The AutoGen adapter supports both transport protocols, allowing you to connect to your Vinkius-hosted server over secure HTTP.

You can program a critic agent to compare outputs from `plan_bus_route` and `list_bicimad_stations` to decide if a bus or a bike is the safer bet during rush hour.

Yes. Your access tokens and routing queries are processed within Vinkius's zero-trust sandboxed environment, ensuring your private transit choices remain confidential.

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