How to integrate Digital ocean MCP with Pydantic AI

Framework Integration Gradient
Digital ocean Logo
Pydantic AI Logo
divider

Introduction

This guide walks you through connecting Digital ocean to Pydantic AI 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 Pydantic AI 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Digital ocean
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Digital ocean workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming

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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Digital ocean
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Digital ocean
  • MCPServerStreamableHTTP connects to the Digital ocean MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Digital ocean
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["digital_ocean"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Digital ocean tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
digital_ocean_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[digital_ocean_mcp],
    instructions=(
        "You are a Digital ocean assistant. Use Digital ocean tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Digital ocean endpoint
  • The agent uses GPT-5 to interpret user commands and perform Digital ocean operations
  • The instructions field defines the agent's role and behavior

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Digital ocean.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Digital ocean API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Digital ocean
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["digital_ocean"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    digital_ocean_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[digital_ocean_mcp],
        instructions=(
            "You are a Digital ocean assistant. Use Digital ocean tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Digital ocean.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

Conclusion

You've built a Pydantic AI agent that can interact with Digital ocean through Composio's Tool Router. With this setup, your agent can perform real Digital ocean actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Digital ocean for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

How to build Digital ocean MCP Agent with another framework

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 Pydantic AI?

Yes, you can. Pydantic AI 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.

Used by agents from

Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.