How to Use the Hetzner MCP in AutoGen
Deploy multi-agent AutoGen teams to debate, plan, and execute Hetzner infrastructure changes.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Hetzner MCP to AutoGen
Create your Vinkius account to connect Hetzner 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.
Multi-Agent Hetzner Provisioning
The Hetzner MCP server gives your AutoGen swarms the ability to manipulate real cloud infrastructure. You assign `create_server` and `create_network` to an execution agent, while a separate security agent reviews the proposed architecture. They debate the deployment plan before writing a single line of state. This conversational approach prevents stupid mistakes. If the execution agent tries to spin up a node without proper SSH keys, the security agent flags the missing `create_ssh_key` step. They negotiate the fix, finalize the configuration, and then execute the API calls in the correct sequence.
Consensus-Driven Firewall Management
Network security requires strict oversight. Your AutoGen setup can feature a networking agent that pulls current rules via `list_firewalls` and proposes modifications. A compliance agent then checks those changes against your internal policies before allowing `create_firewall` to run. The agents handle the back-and-forth automatically. If a developer requests port 80 to be opened, the swarm discusses whether a load balancer is a better approach. They might decide to use `create_load_balancer` instead, routing traffic securely without exposing the raw compute nodes.
Automated Disaster Recovery Drills
Testing backups usually falls to the bottom of the priority list. You can build an AutoGen routine where agents simulate a failure, use `list_storage_box_snapshots` to find a recovery point, and spin up a clone using `rebuild_server`. They verify the recovery without human intervention. One agent acts as the chaos monkey, shutting down instances with `poweron_server` toggles. The recovery agent detects the outage via `get_server` and executes the runbook. You get a complete transcript of their conversation, proving your disaster recovery plan actually works.
Set up Hetzner 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Hetzner tools and returns structured results.
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="Hetzner_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Hetzner data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Hetzner_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Hetzner data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Hetzner Cloud. 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 Hetzner MCP in AutoGen
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