# How to integrate Zeplin MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Zeplin MCP with OpenAI Agents SDK",
  "toolkit": "Zeplin",
  "toolkit_slug": "zeplin",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/zeplin/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/zeplin/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:31:12.652Z"
}
```

## Introduction

This guide walks you through connecting Zeplin to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Zeplin agent that can list all project styleguides in zeplin, get all screens for a specific project, fetch comments from a specific zeplin screen through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Zeplin account through Composio's Zeplin MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Zeplin with

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

The Zeplin MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zeplin account. It provides structured and secure access to your Zeplin workspace, so your agent can perform actions like listing projects, fetching screens, exporting assets, managing components, and collaborating with your design team on your behalf.
- Project and styleguide management: Let your agent list, fetch, or organize your Zeplin projects and associated styleguides for faster design handoff and reference.
- Screen and asset retrieval: Automatically pull screen details, preview images, or export assets from any project directly into your workflow, no copy-paste required.
- Component library access: Have your agent fetch, list, or update components from your shared libraries to keep your design system in sync.
- Commenting and collaboration: Enable your agent to read, create, or manage comments on screens or components, streamlining feedback and design review cycles.
- Resource linking and metadata extraction: Allow your agent to extract, organize, or provide direct links to design resources and metadata, making documentation and developer handoff seamless.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ZEPLIN_AUTH_O_AUTH_AUTHORIZE` | Start OAuth authorization (PKCE) | Tool to start OAuth 2.0 authorization code flow for Zeplin apps. Use when initiating user authorization; call before exchanging the code. |
| `ZEPLIN_CONNECTED_COMPONENTS_PROJECT_LIST` | List Project Connected Components | Tool to list connected components in a Zeplin project. Use when you have the project_id and need to retrieve connected components in a specific project. |
| `ZEPLIN_PROJECT_COLORS_LIST` | List Project Colors | Tool to list colors in a Zeplin project. Use when you need to fetch defined color tokens at the project level after obtaining the project ID. |
| `ZEPLIN_PROJECT_COLOR_UPDATE` | Update Project Color | Tool to update a color in a Zeplin project. Use when you need to modify RGBA channels or source ID of an existing color after confirming the project and color IDs. |
| `ZEPLIN_PROJECTS_GET` | Get Zeplin Project by ID | Tool to get a Zeplin project by ID. Use when you need detailed info about a specific project after confirming its project_id. |
| `ZEPLIN_PROJECTS_MEMBERS_INVITE` | Invite Project Member | Tool to invite a user to a Zeplin project. Use when you need to add a member by email or username to a project after obtaining the project ID. |
| `ZEPLIN_PROJECT_TEXT_STYLES_LIST` | List Project Text Styles | Tool to list text styles in a Zeplin project. Use when you need to fetch typography tokens defined at the project level after obtaining the project ID. |
| `ZEPLIN_PROJECT_TEXT_STYLE_UPDATE` | Update Project Text Style | Tool to update a text style in a Zeplin project. Use when you need to modify typography settings of an existing text style after confirming the project and text style IDs. |
| `ZEPLIN_SCREEN_ANNOTATION_DELETE` | Delete Screen Annotation | Tool to delete a screen annotation in Zeplin. Use when you need to remove a specific annotation from a Zeplin screen given its IDs. |
| `ZEPLIN_SCREEN_ANNOTATION_GET` | Get Screen Annotation | Tool to fetch a single screen annotation. Use when you know the screen_id and annotation_id and need the detailed annotation data. |
| `ZEPLIN_SCREEN_ANNOTATIONS_LIST` | List Screen Annotations | Tool to list annotations for a Zeplin screen. Use when you have the screen_id and need its annotations. |
| `ZEPLIN_SCREEN_ANNOTATIONS_UPDATE` | Update Screen Annotation | Tool to update a screen annotation's content, position, or type. Use after confirming screen_id and annotation_id. |
| `ZEPLIN_SCREEN_COMPONENTS_LIST` | List Screen Components | Tool to list components in a Zeplin screen. Use when you have the screen_id and need to retrieve UI components in a specific screen. |
| `ZEPLIN_SCREEN_SECTION_GET` | Get Screen Section | Tool to get a single screen section. Use when you need to fetch detailed information of a screen section by its ID after confirming the project and section IDs. |
| `ZEPLIN_SCREEN_SECTIONS_LIST` | List Screen Sections | Tool to list screen sections in a Zeplin project. Use when you need a paginated list of screen sections after confirming the project ID. |
| `ZEPLIN_SCREEN_VERSION_GET` | Get Screen Version | Tool to retrieve a specific screen version. Use after specifying both screen_id and version_id when you need detailed snapshot metadata. |
| `ZEPLIN_SCREEN_VERSIONS_CREATE` | Create Screen Version | Tool to create a new version of a screen. Use when uploading a new design snapshot (PNG or JPEG image) as a screen version. Requires a valid project_id, screen_id, and an image file. Optionally include a commit_message. |
| `ZEPLIN_SCREEN_VERSIONS_LIST` | List Screen Versions | Tool to list all versions of a screen. Use when you need to enumerate past screen snapshots after obtaining a screen ID. |
| `ZEPLIN_STYLEGUIDE_COLOR_CREATE` | Create Styleguide Color | Tool to create a new styleguide color. Use after obtaining the styleguide ID to define custom color tokens. |
| `ZEPLIN_STYLEGUIDE_COLORS_LIST` | List Styleguide Colors | Tool to list colors in a Zeplin styleguide. Use when you need to fetch defined color tokens after obtaining the styleguide ID. |
| `ZEPLIN_STYLEGUIDE_COLOR_UPDATE` | Update Styleguide Color | Tool to update a color in a Zeplin styleguide. Use after obtaining the styleguide and color IDs. |
| `ZEPLIN_STYLEGUIDE_TEXT_STYLES_LIST` | List Styleguide Text Styles | Tool to list text styles in a Zeplin styleguide. Use when you need to fetch defined typography tokens after obtaining the styleguide ID. |
| `ZEPLIN_STYLEGUIDE_TEXT_STYLE_UPDATE` | Update Styleguide Text Style | Tool to update a text style in a Zeplin styleguide. Use when you need to modify typography settings of an existing text style after confirming the styleguide and text style IDs. |
| `ZEPLIN_USERS_GET_PERSONAL_PROJECTS` | List Personal Projects | Tool to list personal projects. Use when you need to fetch all projects in the current user's personal workspace after authentication. |

## Supported Triggers

None listed.

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

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

mcp_url = session.mcp.url
```

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

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

## Related Toolkits

- [Figma](https://composio.dev/toolkits/figma) - Figma is a collaborative interface design tool for teams and individuals. It streamlines design workflows with real-time collaboration and easy sharing.
- [Abyssale](https://composio.dev/toolkits/abyssale) - Abyssale is a creative automation platform for generating images, videos, GIFs, PDFs, and HTML5 content programmatically. It streamlines and scales visual content production for marketing, design, and operations teams.
- [Alttext ai](https://composio.dev/toolkits/alttext_ai) - AltText.ai is a service that generates alt text for images automatically. It helps boost accessibility and SEO for your visual content.
- [Bannerbear](https://composio.dev/toolkits/bannerbear) - Bannerbear is an API-driven platform for generating images and videos automatically at scale. It helps businesses create custom graphics, social visuals, and marketing assets using powerful templates.
- [Canva](https://composio.dev/toolkits/canva) - Canva is a drag-and-drop design suite for creating professional graphics, presentations, and marketing materials. It makes it easy for anyone to design with beautiful templates and a vast library of elements.
- [Claid ai](https://composio.dev/toolkits/claid_ai) - Claid.ai delivers AI-driven image editing APIs for tasks like background removal, upscaling, and color correction. It helps automate and enhance image workflows with powerful, developer-friendly tools.
- [Cloudinary](https://composio.dev/toolkits/cloudinary) - Cloudinary is a cloud-based platform for managing, uploading, and transforming images and videos. It streamlines media workflows and delivers optimized assets globally.
- [Cults](https://composio.dev/toolkits/cults) - Cults is a digital marketplace for 3D printing models, connecting designers and makers. It lets creators share, sell, and discover a huge variety of printable designs easily.
- [DeepImage](https://composio.dev/toolkits/deepimage) - DeepImage is an AI-powered image enhancer and upscaler. Get higher-quality images with just a few clicks.
- [Dreamstudio](https://composio.dev/toolkits/dreamstudio) - DreamStudio is Stability AI’s platform for generating and editing images with AI. It lets you easily turn ideas into stunning visuals, fast.
- [Dynapictures](https://composio.dev/toolkits/dynapictures) - Dynapictures is a cloud-based platform for generating personalized images at scale. Instantly create hundreds of custom visuals using your data sources, like Google Sheets.
- [Fal.ai](https://composio.dev/toolkits/fal_ai) - Fal.ai is a generative media platform offering 600+ AI models for images, video, voice, and audio. Developers use Fal.ai for fast, scalable access to cutting-edge generative AI tools.
- [Gamma](https://composio.dev/toolkits/gamma) - Gamma is an AI-powered platform for making beautiful, interactive presentations and documents. It lets anyone create and share engaging decks with minimal effort.
- [Html to image](https://composio.dev/toolkits/html_to_image) - Html to image converts HTML and CSS into images or captures web page screenshots. Instantly generate visuals from code or web content—no manual screenshots needed.
- [Imagior](https://composio.dev/toolkits/imagior) - Imagior is an AI-powered image generation platform that lets you create and customize images using dynamic templates and APIs. Perfect for businesses and creators needing fast, scalable visuals without design hassle.
- [Imejis io](https://composio.dev/toolkits/imejis_io) - Imejis io is an API-based image generation platform with powerful customization and template support. It lets you create and modify images in seconds, no manual design work required.
- [Imgix](https://composio.dev/toolkits/imgix) - Imgix is a real-time image processing and delivery service for developers. It helps you optimize, transform, and deliver images efficiently at any scale.
- [Kraken io](https://composio.dev/toolkits/kraken_io) - Kraken.io is an image optimization and compression platform. It helps you shrink image file sizes while keeping visual quality intact.
- [Logo dev](https://composio.dev/toolkits/logo_dev) - Logo.dev is an API and database for high-resolution company logos and brand metadata. Instantly fetch official logos from any domain without scraping or manual searching.
- [Miro](https://composio.dev/toolkits/miro) - Miro is a collaborative online whiteboard platform for teams to brainstorm, design, and manage projects visually. It streamlines teamwork by enabling real-time idea sharing, diagramming, and workflow planning in a single space.

## Frequently Asked Questions

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

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

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

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

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[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)