How to integrate OpenUI Cloud MCP with Pydantic AI

This guide walks you through connecting OpenUI Cloud to Pydantic AI 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 Pydantic AI 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.

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 Pydantic AI 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 Pydantic AI 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

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for OpenUI Cloud
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your OpenUI Cloud workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like OpenUI Cloud
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to OpenUI Cloud
  • MCPServerStreamableHTTP connects to the OpenUI Cloud MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for OpenUI Cloud
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["openui"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to OpenUI Cloud 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
openui_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[openui_mcp],
    instructions=(
        "You are a OpenUI Cloud assistant. Use OpenUI Cloud tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the OpenUI Cloud endpoint
  • The agent uses GPT-5 to interpret user commands and perform OpenUI Cloud operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with OpenUI Cloud.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • OpenUI Cloud API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for OpenUI Cloud
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["openui"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    openui_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[openui_mcp],
        instructions=(
            "You are a OpenUI Cloud assistant. Use OpenUI Cloud tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with OpenUI Cloud.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

Conclusion

You've built a Pydantic AI agent that can interact with OpenUI Cloud through Composio's Tool Router. With this setup, your agent can perform real OpenUI Cloud actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + OpenUI Cloud for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
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.

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. Pydantic AI 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.

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