How to integrate Bunnycdn MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Bunnycdn to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Bunnycdn agent that can create a new pull zone for static assets, list all dns zones in my bunnycdn account, delete a storage zone by its id, get details for a specific pull zone through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Bunnycdn account through Composio's Bunnycdn 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 necessary dependencies
  • Initialize Composio and create a Tool Router session for Bunnycdn
  • Configure an AI agent that can use Bunnycdn as a tool
  • Run a live chat session where you can ask the agent to perform Bunnycdn operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

The Bunnycdn MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bunnycdn account. It provides structured and secure access to your CDN resources, so your agent can perform actions like managing storage zones, configuring DNS records, creating pull zones, and retrieving zone details on your behalf.

  • Effortless storage zone management: Instantly add or delete storage zones in specific regions, letting your agent optimize file storage based on your needs.
  • Automated DNS configuration: Direct your agent to create, update, or remove DNS records and zones, helping you keep your domain setup fast and flexible.
  • Pull zone creation and removal: Have your agent set up new pull zones or clean up unused ones, streamlining your content delivery workflows with minimal manual intervention.
  • Detailed configuration and status retrieval: Ask your agent to fetch comprehensive details for any DNS or pull zone, ensuring you always have up-to-date insights into your CDN setup.
  • Full account overview and auditing: Let the agent list all your DNS zones and pull critical stats, making it easy to audit or review your Bunnycdn resources on demand.

Supported Tools & Triggers

Tools
Add Storage ZoneTool to add a new storage zone.
Create DNS RecordTool to create a new dns record in a specific dns zone.
Create Pull ZoneTool to create a new pull zone.
Delete DNS RecordTool to delete a specific dns record by its id.
Delete DNS ZoneTool to delete a specific dns zone by its id.
Delete Pull ZoneTool to delete a specific pull zone by its id.
Delete Storage ZoneTool to delete a storage zone.
Get DNS Zone DetailsTool to retrieve details of a specific dns zone by its id.
Get DNS Zone ListTool to list all dns zones in your bunny cdn account.
Get Pull ZoneTool to retrieve details of a specific pull zone.
Get Pull Zone ListTool to fetch the list of pull zones.
Get Storage Zone DetailsTool to retrieve the full details of a storage zone.
Get Storage Zone ListTool to list all storage zones in your bunny cdn account.
Get Storage Zone RegionTool to retrieve the region code of a storage zone.
List DNS RecordsTool to list all dns records in a specific dns zone.
Purge Pull ZoneTool to purge the entire cache of a pull zone.
Purge URLTool to purge a specific url from the bunnycdn cache.
Set Storage Zone RegionTool to update replication regions of a storage zone.
Update Pull ZoneTool to update settings for a specific pull zone.
Update Storage ZoneTool to update settings for a specific storage zone.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Bunnycdn project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Bunnycdn.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Bunnycdn Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["bunnycdn"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only bunnycdn.
  • The router checks the user's Bunnycdn connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Bunnycdn.
  • This approach keeps things lightweight and lets the agent request Bunnycdn tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Bunnycdn. "
        "Help users perform Bunnycdn operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Bunnycdn and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Bunnycdn operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Bunnycdn.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Bunnycdn and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["bunnycdn"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Bunnycdn. "
        "Help users perform Bunnycdn operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Bunnycdn MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Bunnycdn.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Bunnycdn MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Bunnycdn MCP with Claude Agent SDK

Google ADK

Google ADK

Use Bunnycdn MCP with Google ADK

LangChain

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Use Bunnycdn MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Bunnycdn MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Bunnycdn MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Bunnycdn MCP with LlamaIndex

CrewAI

CrewAI

Use Bunnycdn MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Bunnycdn MCP?

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

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Bunnycdn tools.

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

Yes, absolutely. You can configure which Bunnycdn 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 Bunnycdn data and credentials are handled as safely as possible.

Used by agents from

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