How to integrate Imagekit io MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Imagekit io to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Imagekit io agent that can move all event photos to new 2024 folder, delete outdated logo file from media library, create custom metadata field for copyright info, copy marketing assets folder to backup location through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Imagekit io account through Composio's Imagekit io 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 Imagekit io
  • Configure an AI agent that can use Imagekit io as a tool
  • Run a live chat session where you can ask the agent to perform Imagekit io 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 Imagekit io MCP server, and what's possible with it?

The Imagekit io MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your ImageKit.io account. It provides structured and secure access to your media library, so your agent can perform actions like organizing folders, managing files, handling bulk operations, editing metadata, and cleaning up assets on your behalf.

  • Bulk file operations: Effortlessly move, copy, or update tags on multiple files at once to streamline large-scale asset management.
  • Folder organization and management: Ask your agent to create new folders for better asset structuring or delete old folders—including all their contents—when you need to tidy up.
  • Custom metadata control: Let your agent create or delete custom metadata fields, so your media assets stay rich with the information your workflows need.
  • File and version cleanup: Instruct the agent to permanently delete files or remove outdated file versions to keep your storage lean and organized.
  • Bulk job monitoring: Have your agent track the status of ongoing bulk jobs, like folder copies or moves, so you always know what’s happening behind the scenes.

Supported Tools & Triggers

Tools
Bulk Job StatusTool to check status of a bulk job.
Bulk Move FilesTool to move multiple files in bulk.
Bulk Remove TagsTool to remove tags from multiple files in bulk.
Copy FolderTool to initiate a bulk copy of a folder.
Create Custom Metadata FieldTool to create a custom metadata field.
Create FolderTool to create a new folder.
Delete Custom Metadata FieldTool to delete a custom metadata field.
Delete FileTool to delete a file.
Delete File VersionTool to delete a specific non-current file version.
Delete FolderTool to delete a folder.
Delete Multiple FilesTool to delete multiple files.
Get Upload Authentication ParametersTool to generate authentication parameters for client-side file uploads.
Get File DetailsTool to retrieve details of a specific file.
Get File MetadataTool to retrieve metadata of an uploaded file.
Get File Version DetailsTool to retrieve details of a specific file version.
Get UsageTool to retrieve account usage metrics.
List and Search AssetsTool to list and search assets in your ImageKit account.
List Custom Metadata FieldsTool to list all custom metadata fields.
List File VersionsTool to list all versions of a file.
Move FolderTool to initiate a bulk move of a folder.
Purge ImageKit CacheTool to purge CDN and ImageKit caches for a given URL.
Check purge cache statusTool to check the status of a cache purge request.
Rename FileTool to rename a file.
Restore File VersionTool to restore a specific non-current file version as the current one.
Update Custom Metadata FieldTool to update an existing custom metadata field.
Update File DetailsTool to update details of a file.

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 Imagekit io 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 Imagekit io.

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 Imagekit io Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["imagekit_io"]
)

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 imagekit_io.
  • The router checks the user's Imagekit io connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Imagekit io.
  • This approach keeps things lightweight and lets the agent request Imagekit io 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 Imagekit io. "
        "Help users perform Imagekit io 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 Imagekit io 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 Imagekit io 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 Imagekit io.
  • 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 Imagekit io 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=["imagekit_io"]
)
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 Imagekit io. "
        "Help users perform Imagekit io 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 Imagekit io MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Imagekit io.

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 Imagekit io MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Imagekit io MCP with Claude Agent SDK

Google ADK

Google ADK

Use Imagekit io MCP with Google ADK

LangChain

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Use Imagekit io MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Imagekit io MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Imagekit io MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Imagekit io MCP with LlamaIndex

CrewAI

CrewAI

Use Imagekit io MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Imagekit io MCP?

With a standalone Imagekit io MCP server, the agents and LLMs can only access a fixed set of Imagekit io tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Imagekit io 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 Imagekit io tools.

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

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

Used by agents from

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