How to integrate Digital ocean MCP with Autogen

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Introduction

This guide walks you through connecting Digital ocean to AutoGen using the Composio tool router. By the end, you'll have a working Digital ocean agent that can spin up a droplet for staging environment, provision a new postgresql database cluster, create a dns a record for my domain, add my ssh key to all droplets through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Digital ocean account through Composio's Digital ocean MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Digital ocean
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Digital ocean tools
  • Run a live chat loop where you ask the agent to perform Digital ocean operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Digital ocean MCP server, and what's possible with it?

The Digital ocean MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your DigitalOcean account. It provides structured and secure access to your cloud infrastructure, so your agent can perform actions like creating droplets, managing domains and DNS, provisioning databases, and organizing resources on your behalf.

  • Automated droplet provisioning: Instantly spin up new virtual machines (droplets) by specifying name, region, size, and image to quickly scale your infrastructure.
  • Database and block storage management: Have your agent create managed database clusters or persistent block storage volumes with custom configurations for seamless backend scaling.
  • Domain and DNS record automation: Simplify domain setup and DNS management by letting your agent create new domains and add or update DNS records as needed.
  • Kubernetes and firewall setup: Easily deploy Kubernetes clusters and configure firewalls by defining rules, regions, and node pools—without manual dashboard work.
  • SSH key and resource tagging: Register new SSH keys for secure access or organize your infrastructure with custom tags, making resource management effortless and consistent.

Supported Tools & Triggers

Tools
Create Custom ImageTool to create a new custom image by providing a url to a linux vm image.
Create Database ClusterTool to create a new managed database cluster.
Create New Block Storage VolumeTool to create a new block storage volume.
Create New DomainTool to create a new domain.
Create Domain RecordTool to create a new dns record for a domain.
Create New DropletTool to create a new droplet.
Create New FirewallTool to create a new firewall.
Create New Kubernetes ClusterTool to create a new kubernetes cluster.
Create New SSH KeyTool to create a new ssh key.
Create New TagTool to create a new tag.
Create New VPCTool to create a new vpc.
Delete Block Storage VolumeTool to delete a block storage volume by id.
Delete Database ClusterTool to delete a database cluster by uuid.
Delete DomainTool to delete a domain by name.
Delete Domain RecordTool to delete a dns record by its record id for a domain.
Delete Existing DropletTool to delete a droplet by id.
Delete FirewallTool to delete a firewall by id.
Delete ImageTool to delete a snapshot or custom image by id.
Delete Load BalancerTool to delete a load balancer instance by id.
Delete SSH KeyTool to delete a public ssh key.
Delete TagTool to delete a tag by name.
Delete VPCTool to delete a vpc by its id.
Create New Load BalancerTool to create a new load balancer.
List Domain RecordsTool to list all dns records for a domain.
List All DatabasesTool to list all managed database clusters on your account.
List All DomainsTool to list all domains in your digitalocean account.
List All DropletsTool to list all droplets in your account.
List All FirewallsTool to list all firewalls on your digitalocean account.
List All ImagesTool to list all images available on your account.
List All Kubernetes ClustersTool to list all kubernetes clusters on your account.
List All Load BalancersTool to list all load balancer instances on your account.
List All SnapshotsTool to list all snapshots available on your digitalocean account.
List All SSH KeysTool to list all ssh keys in your account.
List All TagsTool to list all tags in your account.
List All VolumesTool to list all block storage volumes available on your account.
List All VPCsTool to list all vpcs on your account.
List Database OptionsTool to list valid database engine, version, region, and size options.
Retrieve DomainTool to retrieve details about a specific domain by its name.
Retrieve Domain RecordTool to retrieve a specific dns record for a domain by its record id.
Retrieve Existing DropletTool to show information about an individual droplet by id.
Retrieve Existing ImageTool to retrieve information about an image by id or slug.
Retrieve TagTool to retrieve an individual tag by name.
Retrieve VPCTool to retrieve details about a specific vpc by its id.
Tag ResourceTool to tag resources by name.
Untag ResourceTool to untag resources by tag name.
Update Domain RecordTool to update an existing dns record for a domain.
Update VPCTool to update information about a vpc.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Digital ocean account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Digital ocean via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Digital ocean connections to use

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Digital ocean session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["digital_ocean"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Digital ocean tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Digital ocean assistant agent with MCP tools
    agent = AssistantAgent(
        name="digital_ocean_assistant",
        description="An AI assistant that helps with Digital ocean operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Digital ocean tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Digital ocean related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Digital ocean tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Digital ocean and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Digital ocean session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["digital_ocean"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Digital ocean assistant agent with MCP tools
        agent = AssistantAgent(
            name="digital_ocean_assistant",
            description="An AI assistant that helps with Digital ocean operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Digital ocean related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Digital ocean through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Digital ocean, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Digital ocean MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Digital ocean MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Digital ocean MCP with Claude Agent SDK

Google ADK

Google ADK

Use Digital ocean MCP with Google ADK

LangChain

LangChain

Use Digital ocean MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Digital ocean MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Digital ocean MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Digital ocean MCP with LlamaIndex

CrewAI

CrewAI

Use Digital ocean MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Digital ocean MCP?

With a standalone Digital ocean MCP server, the agents and LLMs can only access a fixed set of Digital ocean tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Digital ocean and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Autogen?

Yes, you can. Autogen fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Digital ocean tools.

Can I manage the permissions and scopes for Digital ocean while using Tool Router?

Yes, absolutely. You can configure which Digital ocean scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Digital ocean data and credentials are handled as safely as possible.

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