# How to integrate RunPod MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate RunPod MCP with OpenAI Agents SDK",
  "toolkit": "RunPod",
  "toolkit_slug": "runpod",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/runpod/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/runpod/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-03-29T06:48:32.592Z"
}
```

## Introduction

This guide walks you through connecting RunPod to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working RunPod agent that can launch a new gpu pod for inference, get status of all active pods, stop a running pod with id 12345 through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a RunPod account through Composio's RunPod MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate RunPod with

- [ChatGPT](https://composio.dev/toolkits/runpod/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/runpod/framework/antigravity)
- [Claude Agent SDK](https://composio.dev/toolkits/runpod/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/runpod/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/runpod/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/runpod/framework/codex)
- [Cursor](https://composio.dev/toolkits/runpod/framework/cursor)
- [VS Code](https://composio.dev/toolkits/runpod/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/runpod/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/runpod/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/runpod/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/runpod/framework/cli)
- [Google ADK](https://composio.dev/toolkits/runpod/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/runpod/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/runpod/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/runpod/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/runpod/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/runpod/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 RunPod
- Configure an AI agent that can use RunPod as a tool
- Run a live chat session where you can ask the agent to perform RunPod 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 RunPod MCP server, and what's possible with it?

The RunPod MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your RunPod account. It provides structured and secure access so your agent can perform RunPod operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `RUNPOD_CREATE_CLUSTER` | Create RunPod Cluster | Tool to create a new GPU cluster for multi-node distributed computing workloads on RunPod. Use when you need to deploy multiple pods with shared configuration for parallel processing, ML training, or HPC workloads. |
| `RUNPOD_CREATE_SECRET` | Create Secret | Tool to create a new secure secret in RunPod for credential management. Use when you need to store sensitive values like API keys, passwords, or tokens that will be accessible in pods and endpoints via environment variables (RUNPOD_SECRET_). |
| `RUNPOD_DELETE_REGISTRY_AUTH` | Delete Container Registry Authentication | Tool to delete container registry authentication from RunPod. Use when you need to remove stored registry credentials. |
| `RUNPOD_DELETE_TEMPLATE` | Delete Template | Tool to remove a RunPod template via GraphQL mutation. Use when you need to delete a template that is no longer needed. The template must not be in use by any pods or assigned to any serverless endpoints, otherwise the operation will fail. |
| `RUNPOD_GET_GPU_TYPES` | Get GPU Types | Tool to retrieve available GPU types and their specifications, pricing, and availability from RunPod. Use when you need to find GPU options for deployment. |
| `RUNPOD_GET_AUTHENTICATED_USER_INFO` | Get authenticated user info | Retrieve basic information about the authenticated user including ID, email, and security settings. Use this to get the current user's ID, email address, terms of service status, and MFA settings. Note: Access to financial fields (balance, spending, etc.) requires elevated API key permissions. |
| `RUNPOD_GET_POD_DETAILS` | Get Pod Details | Retrieve details of a specific RunPod pod by its unique pod ID. Returns pod configuration including GPU count, memory, cost, and status. Use when you need to check the current state or configuration of an existing pod. |
| `RUNPOD_LIST_CPU_TYPES` | List CPU Types | Tool to retrieve available CPU types and their specifications from RunPod. Use when you need to view CPU options for provisioning pods or selecting hardware configurations. |
| `RUNPOD_SAVE_SERVERLESS_ENDPOINT` | Save Serverless Endpoint | Tool to create or update a RunPod serverless endpoint with GPU configuration and scaling settings. Use when configuring new GPU-accelerated serverless endpoints or modifying existing endpoint parameters. Include 'id' parameter to update an existing endpoint, omit it to create a new one. |
| `RUNPOD_SAVE_CONTAINER_REGISTRY_AUTHENTICATION` | Save Container Registry Authentication | Tool to save container registry authentication credentials for accessing private Docker images in RunPod. Use when you need to store credentials for a private container registry. |
| `RUNPOD_SAVE_TEMPLATE` | Save Template | Tool to create a new RunPod template or update an existing one with container configuration. Use when you need to define reusable pod/serverless configurations with specific images, environment variables, and resource allocations. For serverless templates, always set volumeInGb to 0. |
| `RUNPOD_UPDATE_REGISTRY_AUTH` | Update Registry Auth | Tool to update existing container registry authentication credentials in RunPod. Use when you need to modify the username or password for an existing registry authentication. |
| `RUNPOD_UPDATE_USER_SETTINGS` | Update User Settings | Tool to update current user settings (e.g., SSH public key) in RunPod. Use when you need to configure SSH access to pods by setting the user's SSH public key. |

## Supported Triggers

None listed.

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

The RunPod MCP server is an implementation of the Model Context Protocol that connects your AI agent to RunPod. It provides structured and secure access so your agent can perform RunPod 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 RunPod 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 RunPod.
```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 runpod.
- The router checks the user's RunPod connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access RunPod.
- This approach keeps things lightweight and lets the agent request RunPod tools only when needed during the conversation.
```python
# Create a RunPod Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["runpod"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for RunPod
const session = await composio.create(userId as string, {
  toolkits: ['runpod'],
});
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 RunPod. "
        "Help users perform RunPod 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 RunPod. Help users perform RunPod 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=["runpod"]
)
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 RunPod. "
        "Help users perform RunPod 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: ['runpod'],
  });
  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 RunPod. Help users perform RunPod 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 RunPod MCP with OpenAI Agents SDK to build a functional AI agent that can interact with RunPod.
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 RunPod MCP Agent with another framework

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

## Related Toolkits

- [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.
- [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.
- [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.
- [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.
- [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows.
- [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application.
- [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities.
- [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization.
- [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications.
- [Apipie ai](https://composio.dev/toolkits/apipie_ai) - Apipie ai is an AI model aggregator offering a single API for accessing top AI models from multiple providers. It helps developers build cost-efficient, latency-optimized AI solutions without juggling multiple integrations.
- [Astica ai](https://composio.dev/toolkits/astica_ai) - Astica ai provides APIs for computer vision, NLP, and voice synthesis. Integrate advanced AI features into your app with a single API key.
- [Bigml](https://composio.dev/toolkits/bigml) - BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient.
- [Botbaba](https://composio.dev/toolkits/botbaba) - Botbaba is a platform for building, managing, and deploying conversational AI chatbots across messaging channels. It streamlines chatbot automation, making it easier to integrate AI into customer interactions.
- [Botpress](https://composio.dev/toolkits/botpress) - Botpress is an open-source platform for building, deploying, and managing chatbots. It helps teams automate conversations and deliver rich, interactive messaging experiences.
- [Chatbotkit](https://composio.dev/toolkits/chatbotkit) - Chatbotkit is a platform for building and managing AI-powered chatbots using robust APIs and SDKs. It lets you easily add conversational AI to your apps for better user engagement.
- [Cody](https://composio.dev/toolkits/cody) - Cody is an AI assistant built for businesses, trained on your company's knowledge and data. It delivers instant answers and insights, tailored for your team.
- [Context7 MCP](https://composio.dev/toolkits/context7_mcp) - Context7 MCP delivers live, version-specific code docs and examples right from the source. It helps developers and AI agents instantly retrieve authoritative programming info—no more out-of-date docs.
- [Customgpt](https://composio.dev/toolkits/customgpt) - CustomGPT.ai lets you build and deploy chatbots tailored to your own data and business needs. Get precise and context-aware AI conversations without writing code.
- [Datarobot](https://composio.dev/toolkits/datarobot) - Datarobot is a machine learning platform that automates model development, deployment, and monitoring. It empowers organizations to quickly gain predictive insights from large datasets.
- [Deepgram](https://composio.dev/toolkits/deepgram) - Deepgram is an AI-powered speech recognition platform for accurate audio transcription and understanding. It enables fast, scalable speech-to-text with advanced audio intelligence features.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and RunPod MCP?

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

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

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

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