How to Use the DigitalOcean MCP in AutoGen
Deploy collaborating AutoGen agents to debate and manage your DigitalOcean cloud infrastructure via MCP.
Works with every AI agent you already use
…and any MCP-compatible client
Connect DigitalOcean MCP to AutoGen
Create your Vinkius account to connect DigitalOcean 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.
Run AutoGen agent debates on Droplet configurations
By running `list_cloud_firewalls` and `list_compute_droplets`, this multi-agent setup enables consensus-driven decision making across your DigitalOcean infrastructure. A security agent runs the firewall tools to analyze open ports, while a performance agent runs the compute tools to verify instance sizes, debating the optimal configuration before presenting a final recommendation. This conversational approach ensures that DigitalOcean infrastructure changes are thoroughly vetted by your AutoGen agents. The agents challenge each other's assumptions using raw data from `get_droplet_details`, preventing configuration drift and reducing human oversight.
Coordinate database and app platform audits
This monitoring tool relies on `list_managed_databases` and `list_app_platform_services` to set up dedicated AutoGen agents that track your DigitalOcean databases and applications using this MCP Server. One agent manages the database state, while another tracks application deployments to ensure your web services are properly connected to their backends. The AutoGen agents communicate with each other to verify that database connection strings match active clusters. By automating this cross-agent verification, you can catch misconfigured DigitalOcean environment variables before they trigger production outages.
Analyze storage costs and project boundaries
This financial audit tool runs `list_cloud_projects` and `list_block_storage_volumes` to optimize your DigitalOcean cloud spend by letting AutoGen agents debate resource allocation. An analyst agent maps out logical boundaries, while a storage agent identifies orphaned disks that are running up your monthly bill. The AutoGen agents negotiate which volumes can be safely flagged for deletion based on active project associations. This collaborative audit gives your engineering team a clear, justified list of cost-saving recommendations for your DigitalOcean footprint without manual checking.
Set up DigitalOcean 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 DigitalOcean 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="DigitalOcean_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent DigitalOcean 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="DigitalOcean_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent DigitalOcean 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 DigitalOcean. 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 DigitalOcean MCP in AutoGen
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