# How to integrate Cloudlayer MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Cloudlayer MCP with OpenAI Agents SDK",
  "toolkit": "Cloudlayer",
  "toolkit_slug": "cloudlayer",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/cloudlayer/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/cloudlayer/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:06:50.160Z"
}
```

## Introduction

This guide walks you through connecting Cloudlayer to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Cloudlayer agent that can generate pdf from a contract html template, convert a marketing webpage to a png image, list your most recent generated assets through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Cloudlayer account through Composio's Cloudlayer MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Cloudlayer with

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

The Cloudlayer MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Cloudlayer account. It provides structured and secure access to dynamic document and asset generation, so your agent can perform actions like converting HTML or URLs to PDFs or images, managing assets, and configuring storage on your behalf.
- Automated PDF and image generation: Instantly convert HTML content or public URLs into professional PDFs and images for reporting, documentation, or sharing.
- Asset management and retrieval: Let your agent fetch metadata or download links for generated assets, or list your most recent document and image creations.
- Dynamic storage configuration: Seamlessly add and manage external storage buckets or containers for organizing generated files and assets.
- Real-time API health monitoring: Enable your agent to check Cloudlayer API status, ensuring your integrations are always up and running.
- Flexible screenshot and rendering tasks: Capture dynamic webpage screenshots as images or PDFs, with full control over conversion parameters, for advanced automation workflows.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CLOUDLAYER_ADD_STORAGE` | Add Storage | Add a user-owned S3-compatible storage configuration for storing generated assets. This action allows Enterprise plan users to configure their own S3-compatible storage (AWS S3, DigitalOcean Spaces, Wasabi, MinIO, etc.) instead of using the built-in cloud storage included with Cloudlayer accounts. Note: User storage is only available on Enterprise plans. Standard plans will receive an 'allowed: false' response indicating the feature requires a plan upgrade. |
| `CLOUDLAYER_CONVERT_HTML_TO_IMAGE` | Convert HTML to Image (V2) | Convert HTML content to an image (PNG, JPG, or WebP) using the v2 API endpoint. Renders the provided HTML string using a headless browser and returns job details with the generated image asset. Supports various rendering options including viewport configuration, transparency, auto-scroll, and custom wait conditions. |
| `CLOUDLAYER_CONVERT_HTML_TO_PDF_V2` | Convert HTML to PDF (v2) | Tool to convert HTML content to PDF using CloudLayer v2 API. Use when you need to generate a PDF from raw HTML with advanced options like custom paper size, margins, headers/footers, and viewport settings. The HTML is automatically Base64 encoded before sending to the API. |
| `CLOUDLAYER_CONVERT_URL_TO_PDF_GET` | Convert URL to PDF (Simple) | Tool to convert a URL to PDF using GET request. Use when you need quick PDF conversion with minimal parameters and immediate result. |
| `CLOUDLAYER_DELETE_STORAGE` | Delete Storage Configuration | Tool to delete a specific user storage configuration. Use when you need to remove an external bucket configuration by its ID after confirming the ID is correct. |
| `CLOUDLAYER_GET_ACCOUNT_INFO` | Get Account Info | Tool to retrieve Cloudlayer account usage, credits, and document counts. Use when monitoring account limits and subscription status. |
| `CLOUDLAYER_GET_ASSET` | Get Asset | Tool to retrieve a specific asset by its ID. Use when you need to fetch metadata or download URL of an existing asset after its generation. |
| `CLOUDLAYER_GET_JOB_BY_ID` | Get Job By ID | Retrieve details of a specific Cloudlayer job by its ID. Use this to check the status of an async job, get the asset download URL after completion, or view job parameters. Returns 401 if the job ID doesn't exist or doesn't belong to your account. |
| `CLOUDLAYER_GET_STATUS` | Get API Status | Tool to test API reachability. Use when checking if the Cloudlayer API is available. |
| `CLOUDLAYER_GET_STORAGE_BY_ID` | Get Storage Configuration by ID | Tool to retrieve a specific storage configuration by its ID. Use when you need to inspect or validate details of a user storage configuration. |
| `CLOUDLAYER_LIST_ASSETS` | List Assets | List assets in your CloudLayer account with cursor-based pagination. Returns PDFs and images generated via HTML/URL conversion jobs. Use this to find asset IDs for further operations like downloading or deleting assets. |
| `CLOUDLAYER_LIST_JOBS` | List Jobs | List jobs in your CloudLayer account with cursor-based pagination. Use when you need to view your recent jobs and their statuses. |
| `CLOUDLAYER_LIST_STORAGE` | List Storage Configurations | Retrieves all user storage configurations (S3-compatible buckets) for the authenticated Cloudlayer account. Use this to view configured external storage destinations where generated documents can be saved. Note: User Storage is an Enterprise plan feature. Non-Enterprise accounts will receive an empty list. |
| `CLOUDLAYER_TEMPLATE_TO_PDF` | Template to PDF | Generate a PDF document from an HTML/Nunjucks template with dynamic data. Provide either: - A `templateId` for predefined templates from CloudLayer's template library, OR - A base64-encoded `template` string containing custom HTML/Nunjucks markup. The `data` parameter populates template variables (e.g., {{name}}, {{items}}) with your JSON data. By default, jobs run asynchronously and return a job ID to poll for completion via get_job_by_id. |
| `CLOUDLAYER_URL_TO_IMAGE_POST` | Convert URL to Image | Converts a webpage URL to an image (PNG, JPG, or WebP). Supports custom viewport settings, wait conditions, transparency, auto-scroll, and thumbnail preview generation. The API is asynchronous - use the returned job ID to poll for results. |
| `CLOUDLAYER_URL_TO_PDF_POST` | Convert URL to PDF | Tool to convert a URL to PDF with full parameter support. Use when you need advanced control over paper size, margins, headers/footers, or webhook callbacks. |

## Supported Triggers

None listed.

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

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

mcp_url = session.mcp.url
```

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

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

## Related Toolkits

- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze.
- [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization.
- [Affinda](https://composio.dev/toolkits/affinda) - Affinda is an AI-powered document processing platform that automates data extraction from resumes, invoices, and more. It streamlines document-heavy workflows by turning files into structured, actionable data.
- [Agility cms](https://composio.dev/toolkits/agility_cms) - Agility CMS is a headless content management system for building and managing digital experiences across platforms. It lets teams update content quickly and deliver omnichannel experiences with ease.
- [Algodocs](https://composio.dev/toolkits/algodocs) - Algodocs is an AI-powered platform that automates data extraction from business documents. It delivers fast, secure, and accurate processing without templates or manual training.
- [Api2pdf](https://composio.dev/toolkits/api2pdf) - Api2Pdf is a REST API for generating PDFs from HTML, URLs, and documents using powerful engines like wkhtmltopdf and Headless Chrome. It streamlines document conversion and automation for developers and businesses.
- [Aryn](https://composio.dev/toolkits/aryn) - Aryn is an AI-powered platform for parsing, extracting, and analyzing data from unstructured documents. Use it to automate document processing and unlock actionable insights from your files.
- [Boldsign](https://composio.dev/toolkits/boldsign) - Boldsign is a digital eSignature platform for sending, signing, and tracking documents online. Organizations use it to automate agreements and manage legally binding workflows efficiently.
- [Boloforms](https://composio.dev/toolkits/boloforms) - BoloForms is an eSignature platform built for small businesses, offering unlimited signatures, templates, and forms. It simplifies digital document signing and team collaboration at a predictable, fixed price.
- [Box](https://composio.dev/toolkits/box) - Box is a cloud content management and file sharing platform for businesses. It helps teams securely store, organize, and collaborate on files from anywhere.
- [Carbone](https://composio.dev/toolkits/carbone) - Carbone is a blazing-fast report generator that turns JSON data into PDFs, Word docs, spreadsheets, and more using flexible templates. It lets you automate document creation at scale with minimal code.
- [Castingwords](https://composio.dev/toolkits/castingwords) - CastingWords is a transcription service specializing in human-powered, accurate transcripts via a simple API. Get seamless audio-to-text conversion for interviews, meetings, podcasts, and more.
- [Cloudconvert](https://composio.dev/toolkits/cloudconvert) - CloudConvert is a powerful file conversion service supporting over 200 file formats. It streamlines converting, compressing, and managing documents, media, and more, all in one place.
- [Cloudpress](https://composio.dev/toolkits/cloudpress) - Cloudpress is a content export tool for Google Docs and Notion. It automates publishing to your favorite Content Management Systems.
- [Contentful graphql](https://composio.dev/toolkits/contentful_graphql) - Contentful graphql is a content delivery API that lets you access Contentful data using GraphQL queries. It gives you efficient, flexible ways to fetch and manage structured content for any digital project.
- [Conversion tools](https://composio.dev/toolkits/conversion_tools) - Conversion Tools is an online service for converting documents between formats such as PDF, Word, Excel, XML, and CSV. It lets you automate complex document workflows with just a few clicks.
- [Convertapi](https://composio.dev/toolkits/convertapi) - ConvertAPI is a robust file conversion service for documents, images, and spreadsheets. It streamlines programmatic format changes and lets developers automate complex workflows with a single API.
- [Craftmypdf](https://composio.dev/toolkits/craftmypdf) - CraftMyPDF is a web-based service for designing and generating PDFs with templates and live data. It streamlines document creation by automating personalized PDFs at scale.
- [Docmosis](https://composio.dev/toolkits/docmosis) - Docmosis generates PDF and Word documents from user-defined templates. It's perfect for merging data fields to quickly produce reports, invoices, and business letters.

## Frequently Asked Questions

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

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

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

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

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