How to Use the Caddy Server MCP in AutoGen
Run AutoGen multi-agent debates to safely evaluate, edit, and apply complex Caddy Server routing configurations.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Caddy Server MCP to AutoGen
Create your Vinkius account to connect Caddy Server 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.
Debate config changes using this MCP Server
Proposing changes with `insert_config` lets a security agent and a performance agent debate updates to your reverse proxy setup. One agent drafts the JSON while another reviews it for security flaws. They run `adapt_config` to test the payload before it goes live. This collaborative review process ensures that your production routing logic is thoroughly vetted before any changes are applied.
Coordinate multi-agent upstream failovers
Monitoring healthy backends with `get_upstreams` alerts your network agent when backend nodes go down. The network agent proposes a rerouting plan using `replace_config` to bypass the dead servers. A separate validation agent inspects the new targets before the change is executed. Once consensus is reached, the primary agent calls `load_config` to apply the updated routing rules without dropping active connections.
Manage PKI trust chains via collaborative agents
Inspecting CA health with `get_pki_ca` lets your AutoGen agents automatically manage local certificate authorities using the MCP interface. One agent checks CA health and fetches active certificates with `get_pki_ca_certs` to verify their expiration dates. If a certificate is nearing expiration, the agent alerts your deployment agent to renew it. This keeps your local development environments secure without requiring manual command-line intervention.
Set up Caddy Server 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 Caddy Server 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="Caddy Server_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Caddy Server 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="Caddy Server_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Caddy Server 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 Caddy Server. 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 Caddy Server MCP in AutoGen
Use it with your favorite AI tools
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