# How to integrate Dreamstudio MCP with LangChain

```json
{
  "title": "How to integrate Dreamstudio MCP with LangChain",
  "toolkit": "Dreamstudio",
  "toolkit_slug": "dreamstudio",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/dreamstudio/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/dreamstudio/framework/langchain.md",
  "updated_at": "2026-05-12T10:09:45.548Z"
}
```

## Introduction

This guide walks you through connecting Dreamstudio to LangChain using the Composio tool router. By the end, you'll have a working Dreamstudio agent that can transform your photo into a fantasy landscape, list all available dreamstudio image engines, show your dreamstudio credit balance through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Dreamstudio account through Composio's Dreamstudio MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Dreamstudio with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Dreamstudio project to Composio
- Create a Tool Router MCP session for Dreamstudio
- Initialize an MCP client and retrieve Dreamstudio tools
- Build a LangChain agent that can interact with Dreamstudio
- Set up an interactive chat interface for testing

## What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.
Key features include:
- Agent Framework: Build agents that can use tools and make decisions
- MCP Integration: Connect to external services through Model Context Protocol adapters
- Memory Management: Maintain conversation history across interactions
- Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

## What is the Dreamstudio MCP server, and what's possible with it?

The Dreamstudio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dreamstudio account. It provides structured and secure access to your generative image tools, so your agent can generate images, edit visuals, check available engines, and monitor your account balance—all on your behalf.
- Image generation from prompts or reference: Ask your agent to create unique images based on detailed text prompts or by transforming existing images using Dreamstudio's powerful engines.
- Engine discovery and selection: Effortlessly retrieve a list of available Dreamstudio engines so your agent can choose the best model for your creative task.
- User account insights: Have your agent fetch your Dreamstudio account details, including user ID, email, and profile information, whenever you need them.
- Real-time credit and usage monitoring: Let your agent check your current credit balance and track usage to ensure you always have resources for your next creative project.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DREAMSTUDIO_GENERATE_IMAGE_FROM_IMAGE` | Generate Image from Image | Tool to generate a new image from an initial image and text prompts. Use after you have a reference image and want to transform it via text guidance. |
| `DREAMSTUDIO_GENERATE_IMAGE_FROM_TEXT` | Generate Image from Text | Generate images from text prompts using Stability AI's text-to-image models. Use when you need to create images from textual descriptions without a reference image. Supports multiple prompts with weights, configurable dimensions, and various generation parameters. |
| `DREAMSTUDIO_LIST_ENGINES` | List Engines | List all available DreamStudio/Stability AI engines accessible with your API key. This action retrieves all AI models (engines) you can use for image generation and other tasks. Common engines include Stable Diffusion XL and various Stable Diffusion versions. Use this action to: - Discover which engines are available to your account - Get engine IDs needed for image generation requests - Check engine types and capabilities No parameters required - simply call to get the complete list of accessible engines. Using an unsupported engine_id in generation requests will cause failures; engines also vary in supported image sizes (typically capped near 1024x1024) and quality for specific tasks. |
| `DREAMSTUDIO_USER_ACCOUNT` | User Account | Retrieves authenticated user's account information from Stability AI. Returns user ID, email, organization memberships, and profile picture. No parameters required - uses authenticated session. |
| `DREAMSTUDIO_USER_BALANCE` | DreamStudio User Balance | Retrieves the user's current credit balance from their DreamStudio account. Use this tool to check how many credits are available before generating images or to monitor remaining credits after API operations. Credits are consumed when generating images through the Stability AI API. For large or high-resolution batch generation, verify sufficient balance first — insufficient credits will cause failures mid-run. |

## Supported Triggers

None listed.

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

The Dreamstudio MCP server is an implementation of the Model Context Protocol that connects your AI agent to Dreamstudio. It provides structured and secure access so your agent can perform Dreamstudio 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

No description provided.

### 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).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio's API
- COMPOSIO_USER_ID identifies the user for session management
- OPENAI_API_KEY enables access to OpenAI's language models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

What's happening:
- We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
- Creating a Composio instance that will manage our connection to Dreamstudio tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Dreamstudio tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned session.mcp.url is the MCP server URL that your agent will use
- This approach allows the agent to dynamically load and use Dreamstudio tools as needed
```python
# Create Tool Router session for Dreamstudio
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['dreamstudio']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['dreamstudio']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "dreamstudio-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "dreamstudio-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Dreamstudio related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Dreamstudio related question or task to the agent.\n");

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

rl.prompt();

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

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

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

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

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

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

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

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['dreamstudio']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "dreamstudio-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Dreamstudio related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

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

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['dreamstudio']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "dreamstudio-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Dreamstudio related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\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

You've successfully built a LangChain agent that can interact with Dreamstudio through Composio's Tool Router.
Key features of this implementation:
- Dynamic tool loading through Composio's Tool Router
- Conversation history maintenance for context-aware responses
- Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## How to build Dreamstudio MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/dreamstudio/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/dreamstudio/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/dreamstudio/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/dreamstudio/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/dreamstudio/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/dreamstudio/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/dreamstudio/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/dreamstudio/framework/cli)
- [Google ADK](https://composio.dev/toolkits/dreamstudio/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/dreamstudio/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/dreamstudio/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/dreamstudio/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/dreamstudio/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.
- [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.
- [Mural](https://composio.dev/toolkits/mural) - Mural is a digital whiteboard platform for distributed visual collaboration. It helps teams brainstorm, map ideas, and diagram together in real time.

## Frequently Asked Questions

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

With a standalone Dreamstudio MCP server, the agents and LLMs can only access a fixed set of Dreamstudio tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Dreamstudio and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain 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 Dreamstudio tools.

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

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

---
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