How to Use the Dokku MCP in AutoGen

Get agents to debate your Dokku deployments. Use AutoGen to verify infrastructure changes before execution.

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Connect Dokku MCP to AutoGen

Create your Vinkius account to connect Dokku 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 Dokku with AutoGen

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Multi-agent Dokku management

Have your agents challenge each other on deployment decisions. A security agent can inspect `list_config` results while an operations agent proposes a `ps_scale` change to handle load. This forces a consensus before any action occurs. They ensure that `set_config` updates don't conflict with existing environment constraints or security policies.

Debate-driven infrastructure changes

Use agents to verify command execution. Before running `run_command` for a database migration, your agents confirm the environment state to prevent accidental data loss. This reduces human error. By requiring multiple agents to agree on the necessity of `ps_restart`, you ensure that only verified changes reach your production containers.

Collaborative Dokku diagnostics

Assign one agent to watch `get_logs` while another interprets the output. They work together to isolate the root cause of a service crash without your manual intervention. They converge on a solution faster than a single bot. Once they agree, they can execute `ps_restart` or other corrective measures as a unified team.

Setup guide

Set up Dokku 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 Dokku 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="Dokku_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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Common questions about Dokku MCP in AutoGen

Pass the tool list from the MCP server to your AssistantAgent. The adapter handles the schema translation so your agents can call tools directly.

That is the point. You can configure agents with different goals—like one focused on uptime and one on cost—to find the best scaling strategy.

The MCP server uses a single endpoint token for all communication. Your data remains isolated within the secure Dokku environment.

The conversation log captures every tool call and its output. You can review the debate and the resulting `ps_scale` or `create_app` actions.

You control the tool list passed to the agent. You can easily exclude destructive tools like `destroy_app` to keep your infrastructure safe.

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