# How to integrate Owl protocol MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Owl protocol MCP with OpenAI Agents SDK",
  "toolkit": "Owl protocol",
  "toolkit_slug": "owl_protocol",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/owl_protocol/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/owl_protocol/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:21:05.475Z"
}
```

## Introduction

This guide walks you through connecting Owl protocol to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Owl protocol agent that can deploy new erc721 collection on polygon, fetch project metadata by project id, list all active blockchain projects through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Owl protocol account through Composio's Owl protocol MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Owl protocol with

- [Claude Agent SDK](https://composio.dev/toolkits/owl_protocol/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/owl_protocol/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/owl_protocol/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/owl_protocol/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/owl_protocol/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/owl_protocol/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/owl_protocol/framework/cli)
- [Google ADK](https://composio.dev/toolkits/owl_protocol/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/owl_protocol/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/owl_protocol/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/owl_protocol/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/owl_protocol/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/owl_protocol/framework/crew-ai)

## 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 Owl protocol
- Configure an AI agent that can use Owl protocol as a tool
- Run a live chat session where you can ask the agent to perform Owl protocol operations

## What is OpenAI 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 Owl protocol MCP server, and what's possible with it?

The Owl protocol MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Owl Protocol account. It provides structured and secure access to your Web3 projects, so your agent can perform actions like deploying smart contracts, retrieving project information, and managing collections on supported blockchains—all on your behalf.
- Deploy new ERC721 collections: Instantly have your agent launch new NFT collection contracts, enabling rapid prototyping or production deployments on-chain.
- Retrieve detailed project metadata: Let your agent fetch and surface all relevant details about a specific Web3 project, including status, configuration, and blockchain associations.
- List all accessible projects: Effortlessly pull a comprehensive list of all projects tied to your account, making it easy to manage or audit your entire Web3 portfolio programmatically.
- Automate Web3 app management: Enable your agent to streamline repetitive blockchain development tasks, reducing manual effort and boosting productivity for DApp developers.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `OWL_PROTOCOL_DEPLOY_COLLECTION` | Deploy ERC721 Collection | Tool to deploy a new ERC721 collection contract. Use after creating a project to programmatically deploy the collection on a specified blockchain. |
| `OWL_PROTOCOL_GET_PROJECT_DETAILS` | Get Project Details | Tool to retrieve details of a specific project. Use when you need metadata about a project after authenticating with your API key. |
| `OWL_PROTOCOL_LIST_PROJECTS` | List Projects | Tool to list all projects. Use when you need to retrieve all projects accessible by the authenticated user. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Owl protocol MCP server is an implementation of the Model Context Protocol that connects your AI agent to Owl protocol. It provides structured and secure access so your agent can perform Owl protocol operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Owl protocol project
- Some knowledge of Python or Typescript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

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 Owl protocol.
```python
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
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
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())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only owl_protocol.
- The router checks the user's Owl protocol connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Owl protocol.
- This approach keeps things lightweight and lets the agent request Owl protocol tools only when needed during the conversation.
```python
# Create a Owl protocol Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["owl_protocol"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Owl protocol
const session = await composio.create(userId as string, {
  toolkits: ['owl_protocol'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Owl protocol. "
        "Help users perform Owl protocol 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",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Owl protocol. Help users perform Owl protocol operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
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())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
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=["owl_protocol"]
)
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 Owl protocol. "
        "Help users perform Owl protocol 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())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['owl_protocol'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Owl protocol. Help users perform Owl protocol operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

This was a starter code for integrating Owl protocol MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Owl protocol.
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 Owl protocol MCP Agent with another framework

- [Claude Agent SDK](https://composio.dev/toolkits/owl_protocol/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/owl_protocol/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/owl_protocol/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/owl_protocol/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/owl_protocol/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/owl_protocol/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/owl_protocol/framework/cli)
- [Google ADK](https://composio.dev/toolkits/owl_protocol/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/owl_protocol/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/owl_protocol/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/owl_protocol/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/owl_protocol/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/owl_protocol/framework/crew-ai)

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- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Owl protocol MCP?

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

### Can I manage the permissions and scopes for Owl protocol while using Tool Router?

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

---
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