How to Use the Netrows MCP in AutoGen

Q: How do I configure Netrows tools for an AutoGen agent?

Install autogen-extmcp. Pass your endpoint URL to StreamableHttpServerParams, extract the tools, and hand them to your AssistantAgent constructor.

Give your AutoGen multi-agent systems direct access to Netrows aviation data.

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Connect Netrows MCP to AutoGen

Create your Vinkius account to connect Netrows 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 Netrows with AutoGen

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Perplexity

Resolve logistics conflicts with AutoGen agents

The `get_airport_flights` tool lists every arriving and departing plane at a specific terminal. Your logistics agent pulls this data to identify peak congestion windows at major hubs. A separate routing agent challenges that analysis by calling `search_airports` to find nearby regional alternatives. The two agents debate the tradeoff between landing fees and ground transport times using the MCP Server data to reach a consensus.

Negotiate travel itineraries autonomously

The `get_flight_schedule` tool provides the baseline timetable for routes between two cities. Your travel planning agent uses this to propose an initial itinerary based on departure times. A risk-management agent then runs `get_flight_details` through this MCP Server to check historical delay patterns and current gate statuses. They argue over connection times until they agree on the most reliable booking option.

Balance live tracking with API budgets

The `track_flight` tool delivers real-time altitude and heading data for airborne targets. Your monitoring agent wants to ping this endpoint constantly to maintain a live map. Your finance agent steps in and calls `get_account_usage` to check the remaining API credits. The agents negotiate a polling frequency that keeps the map accurate without burning through the monthly budget.

Setup guide

Set up Netrows 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 Netrows 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="Netrows_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Netrows 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 Netrows. 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 Netrows MCP in AutoGen

Install `autogen-ext[mcp]`. Pass your endpoint URL to `StreamableHttpServerParams`, extract the tools, and hand them to your `AssistantAgent` constructor.

Yes. You just assign specific tools to specific agents. The logistics agent gets the airport endpoints, while the finance agent handles the account usage.

They react based on their system prompts. If one agent detects a delay via `get_flight_details`, it notifies the group. A rebooking agent then automatically searches for alternatives.

The executing agent receives the error message and explains the failure to the group. The agents then converse to determine if they should retry the call or try a different search parameter.

The system strictly handles flight schedules and aircraft registrations. Your multi-agent debates happen locally, while the Vinkius ephemeral environment processes the API calls without logging your internal negotiation logic.

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