How to Use the Fly.io Extended MCP in AutoGen

Q: Can Fly.io Extended and AutoGen prevent accidental deletions?

By requiring multiple agents to agree before calling deleteapp, you add a layer of human-like deliberation. This makes it impossible for a single agent to accidentally wipe your data.

Deploy a team of debating agents in AutoGen to manage infrastructure using the Fly.io Extended MCP server for consensus-driven operations.

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Connect Fly.io Extended MCP to AutoGen

Create your Vinkius account to connect Fly.io Extended 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 Fly.io Extended with AutoGen

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Debate infrastructure changes

Set up a security agent and an operations agent that discuss any proposed `update_machine` call. One focuses on compliance while the other pushes for performance. This prevents hasty changes that could break your production environment. The agents reach a consensus before the Fly.io Extended MCP server executes the command.

Negotiated resource scaling

Let your agents negotiate when to call `extend_volume` or `create_machine`. They analyze the current load and decide if a scale-up is actually required. This prevents runaway billing caused by aggressive auto-scaling. The agents deliberate and only take action when they agree it's necessary for system stability.

Collaborative machine lifecycle management

Multiple agents verify the state of a machine before one of them calls `stop_machine` or `suspend_machine`. They share information to ensure no critical processes are currently running. This creates a multi-layered check for every disruptive action. Your infrastructure management becomes a team effort where every change is scrutinized by your specialized agents.

Setup guide

Set up Fly.io Extended 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 Fly.io Extended 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="Fly.io Extended_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Fly.io Extended 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="Fly.io Extended_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

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Common questions about Fly.io Extended MCP in AutoGen

You pass the tools to your agents, and they use their internal debate logic to decide which tool to call. The Fly.io Extended MCP server executes the agreed-upon actions.

By requiring multiple agents to agree before calling `delete_app`, you add a layer of human-like deliberation. This makes it impossible for a single agent to accidentally wipe your data.

The server handles all communication through a secure, authenticated channel. Only the agents with the correct permissions can access sensitive resource configurations or delete volumes.

It allows for complex, multi-perspective infrastructure management. You get the speed of automation with the caution that comes from a team of debating agents.

Yes, you can configure your agent group to pause and request human approval before executing any destructive tool. This combines automated debate with final human authority.

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