How to integrate Typeform MCP with Autogen

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Introduction

This guide walks you through connecting Typeform to AutoGen using the Composio tool router. By the end, you'll have a working Typeform agent that can list all recent responses for a form, create a new form for event signup, export submissions from my survey to csv through natural language commands.

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

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

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

The Typeform MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Typeform account. It provides structured and secure access so your agent can perform Typeform operations on your behalf.

Supported Tools & Triggers

Tools
Create Account WorkspaceTool to create a new workspace in a specific Typeform account.
Create FormTool to create a new Typeform form with customizable fields, logic, and settings.
Create ImageTool to upload a new image to your Typeform account via base64 encoding or URL.
Create or Update WebhookTool to create a new webhook or update an existing one for a specified Typeform.
Create ThemeTool to create a new custom theme in Typeform with colors, fonts, background, and layout settings.
Create WorkspaceTool to create a new workspace in Typeform.
Delete FormTool to permanently delete a Typeform and all of its responses.
Delete ImageTool to delete an image from your Typeform account.
Delete ResponsesTool to delete specific responses from a Typeform by response IDs.
Delete ThemeTool to delete a theme from your Typeform account.
Delete WebhookTool to delete a webhook configuration from a Typeform form.
Delete WorkspaceTool to delete a workspace from your Typeform account.
Get About MeGet information about the owner account in Typeform.
Get All Response FilesTool to retrieve a compressed archive containing all files that respondents uploaded for a specified form.
Get Background By SizeTool to retrieve a background image by size from Typeform.
Get Choice Image By SizeTool to retrieve a choice image by size from Typeform.
Get FormTool to retrieve a specific form's complete configuration including fields, logic, settings, and theme.
Get Form MessagesTool to retrieve custom messages for a Typeform including button labels, error messages, and UI text.
Get Form ResponsesTool to retrieve form responses from Typeform with filtering by date, pagination, search, and response type.
Get Image By SizeTool to retrieve an image in a specific size from Typeform.
Get ThemeTool to retrieve a specific theme's configuration including colors, fonts, and layout settings.
Get WebhookTool to retrieve a single webhook by specifying both the form ID and webhook tag.
Get WorkspaceTool to retrieve detailed information about a specific workspace including its name, forms, and team members.
List FormsTool to retrieve a list of all forms in your Typeform account with filtering, pagination, and sorting options.
List ImagesTool to retrieve all images in your Typeform account in reverse-chronological order.
List Typeform ThemesTool to retrieve a paginated list of themes in your Typeform account.
List Form WebhooksTool to retrieve all webhooks associated with a specified typeform.
List WorkspacesTool to retrieve all workspaces in a Typeform account with their IDs, names, form counts, and members.
Patch FormTool to partially update a Typeform using JSON Patch operations.
Update Theme (Partial)Tool to partially update a Typeform theme by ID.
Update FormTool to update an existing Typeform by completely replacing its configuration.
Update Form MessagesTool to update custom messages for form UI elements like buttons, errors, and placeholders in Typeform.
Update ThemeTool to update a theme's complete definition in Typeform.
Update WorkspaceTool to update a workspace's name or manage team member access (add/remove members) in Typeform.
Upload VideoInitiate a video upload to Typeform by obtaining a signed upload URL.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

You will need:

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

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.

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 Typeform via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

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 Typeform connections to use

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 Typeform session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["typeform"]
    )
    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 Typeform tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

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

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 Typeform assistant agent with MCP tools
    agent = AssistantAgent(
        name="typeform_assistant",
        description="An AI assistant that helps with Typeform 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 Typeform tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Typeform 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 Typeform 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 Typeform 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 Typeform session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["typeform"]
    )
    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 Typeform assistant agent with MCP tools
        agent = AssistantAgent(
            name="typeform_assistant",
            description="An AI assistant that helps with Typeform 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 Typeform 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 Typeform 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 Typeform, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Typeform MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Typeform MCP?

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

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

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

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