How to integrate OpenUI Cloud MCP with Autogen

This guide walks you through connecting OpenUI Cloud to AutoGen using the Composio tool router. By the end, you'll have a working OpenUI Cloud agent that can generate user interfaces, create conversations, list your artifacts, view conversation items, and rename chats through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a OpenUI Cloud account through Composio's OpenUI Cloud MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Get started for freeGet a demo
OpenUI Cloud logoOpenUI Cloud
Api Key

OpenUI Cloud is Thesys's API platform for generating interactive UIs, conversations, and artifacts. Use it to turn prompts into rich, app-like interfaces through OpenAI-compatible APIs.

8 Tools

Introduction

This guide walks you through connecting OpenUI Cloud to AutoGen using the Composio tool router. By the end, you'll have a working OpenUI Cloud agent that can generate user interfaces, create conversations, list your artifacts, view conversation items, and rename chats through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a OpenUI Cloud account through Composio's OpenUI Cloud MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate OpenUI Cloud with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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 OpenUI Cloud
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call OpenUI Cloud tools
  • Run a live chat loop where you ask the agent to perform OpenUI Cloud 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 OpenUI Cloud MCP server, and what's possible with it?

The OpenUI Cloud MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your OpenUI Cloud account. It provides structured and secure access to generated interfaces, managed conversations, and persisted artifacts, so your agent can generate interactive interfaces, organize conversations, review conversation history, find artifacts, and retrieve renderable content on your behalf.

  • Interactive interface generation: Have your agent turn text or structured instructions into interactive user interface responses.
  • Conversation organization: Let the agent create conversations, list existing ones, rename them, or delete conversations you no longer need.
  • Conversation history review: Direct your agent to read persisted messages and function call activity from a managed conversation.
  • Artifact discovery: Instruct your agent to list saved artifacts and narrow the results by name or artifact type.
  • Renderable artifact retrieval: Have your agent retrieve a saved artifact with its complete renderable content for review or reuse.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A OpenUI Cloud account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to OpenUI Cloud via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

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 OpenUI Cloud connections to use
5

Import dependencies and create Tool Router session

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 OpenUI Cloud session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["openui"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes OpenUI Cloud tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

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")}
)

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
7

Create the model client and agent

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 OpenUI Cloud assistant agent with MCP tools
    agent = AssistantAgent(
        name="openui_assistant",
        description="An AI assistant that helps with OpenUI Cloud operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the OpenUI Cloud tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any OpenUI Cloud 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")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which OpenUI Cloud 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

Complete Code

Here's the complete code to get you started with OpenUI Cloud and AutoGen:

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 OpenUI Cloud session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["openui"]
    )
    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 OpenUI Cloud assistant agent with MCP tools
        agent = AssistantAgent(
            name="openui_assistant",
            description="An AI assistant that helps with OpenUI Cloud 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 OpenUI Cloud 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 OpenUI Cloud 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 OpenUI Cloud, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every OpenUI Cloud action and event your agent gets out of the box.

Create Conversation

Create a managed OpenUI conversation that can receive persisted turns from Generate UI.

Delete Conversation

Permanently delete one managed OpenUI conversation by ID.

Generate UI

Generate an OpenUI response from text or structured Responses API input.

Get Artifact

Retrieve one persisted OpenUI artifact, including its complete renderable content.

List Artifacts

List persisted OpenUI artifacts, optionally filtering by name or artifact kinds, one cursor-controlled page at a time.

List Conversation Items

Read one cursor-controlled page of persisted messages and function-call items from a managed OpenUI conversation.

List Conversations

List managed OpenUI conversations visible to the connected organization, one cursor-controlled page at a time.

Rename Conversation

Change the title of an existing managed OpenUI conversation.

FRAMEWORKS

How to build OpenUI Cloud MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use OpenUI Cloud MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use OpenUI Cloud MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use OpenUI Cloud MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use OpenUI Cloud MCP with Claude Cowork

Codex logo

Codex

Use OpenUI Cloud MCP with Codex

OpenClaw logo

OpenClaw

Use OpenUI Cloud MCP with OpenClaw

Hermes logo

Hermes

Use OpenUI Cloud MCP with Hermes

CLI logo

CLI

Use OpenUI Cloud MCP with CLI

Google ADK logo

Google ADK

Use OpenUI Cloud MCP with Google ADK

LangChain logo

LangChain

Use OpenUI Cloud MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use OpenUI Cloud MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use OpenUI Cloud MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use OpenUI Cloud MCP with LlamaIndex

CrewAI logo

CrewAI

Use OpenUI Cloud MCP with CrewAI

FAQ

Frequently asked questions

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

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 OpenUI Cloud tools.

Yes, absolutely. You can configure which OpenUI Cloud 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.

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 OpenUI Cloud data and credentials are handled as safely as possible.

Start with OpenUI Cloud.It takes 30 seconds.

Managed auth, hosted MCP servers, and every OpenUI Cloud tool your agent needs.Free to start.

Start building
Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREEBOOK A DEMO
agent.aiZoomLettaGleanHubSpotAWSWabi

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies