# How to integrate Cults MCP with Autogen

```json
{
  "title": "How to integrate Cults MCP with Autogen",
  "toolkit": "Cults",
  "toolkit_slug": "cults",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/cults/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/cults/framework/autogen.md",
  "updated_at": "2026-05-12T10:07:53.746Z"
}
```

## Introduction

This guide walks you through connecting Cults to AutoGen using the Composio tool router. By the end, you'll have a working Cults agent that can list your latest uploaded 3d models, share a new 3d file creation link, fetch approved sharing domains for your account through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Cults account through Composio's Cults MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Cults with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Cults
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Cults tools
- Run a live chat loop where you ask the agent to perform Cults operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

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

The Cults MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Cults account. It provides structured and secure access to your Cults digital marketplace, so your agent can perform actions like sharing new 3D creations, executing advanced queries, and managing approved sharing origins for your designs.
- Fetch approved sharing origins: Instantly retrieve the list of domains authorized to share your 3D models, making it easy to manage and validate sharing destinations.
- Automate GraphQL queries and mutations: Use your agent to run powerful GraphQL operations against the Cults API for custom data retrieval or updates—perfect for creators who need flexibility.
- One-click sharing of new creations (FR): Quickly generate pre-filled links to share your latest 3D files on Cults (in French locale), streamlining the publishing workflow for designers.
- Manage digital assets programmatically: Enable your agent to interact with your Cults account to organize, update, or extend your digital portfolio through the available tools.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CULTS_GET_APPROVED_ORIGINS` | Get Approved Origins | Inspects the Cults creation page to detect any sharing origin information. Note: Cults requires origins to be manually approved via support contact before use with the Share on Create feature. This action attempts to parse the creation page for origin-related data but may return empty results. For guaranteed origin information, contact Cults support directly at https://cults3d.com/en/api. |
| `CULTS_GRAPH_QL_POST` | Cults GraphQL POST | Execute GraphQL queries and mutations against the Cults3D API. Cults3D is a marketplace for 3D printable models. This tool provides access to: - Browse and search 3D model designs (creations) - View user profiles and their uploaded models - Access your own account data, sales, and printlists (via 'myself' query) - Manage your creations and discounts (via mutations) The API uses standard GraphQL syntax. Query the schema for available fields. Note: 3D model files themselves are not accessible via the API, only metadata. |
| `CULTS_SHARE_ON_CREATE_FR` | Share on Create (FR) | Generate a one-click share URL for publishing a 3D file to Cults (French locale). This tool constructs a shareable link that, when clicked by users, takes them to the Cults creation page with the 3D file URL pre-filled. This enables seamless sharing of 3D models from your platform to Cults. Prerequisites: - Your site/origin must be pre-approved by Cults for share integration - The file_url must point to a publicly accessible 3D file Note: This action generates the URL without making an API call, so it always succeeds as long as the parameters are valid. Users will need to be logged into Cults to complete the sharing process. |

## Supported Triggers

None listed.

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

The Cults MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Cults. Instead of manually wiring Cults APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Cults account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Cults via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Cults connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Cults tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Cults session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["cults"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Cults tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Cults assistant agent with MCP tools
    agent = AssistantAgent(
        name="cults_assistant",
        description="An AI assistant that helps with Cults operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Cults tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Cults related question or task to the agent.\n")

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Cults session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["cults"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Cults assistant agent with MCP tools
        agent = AssistantAgent(
            name="cults_assistant",
            description="An AI assistant that helps with Cults operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

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

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

## Conclusion

You now have an Autogen assistant wired into Cults through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Cults, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Cults MCP Agent with another framework

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

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

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

Yes, you can. Autogen 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 Cults tools.

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

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

---
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