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Connect Autogen to Typless MCP. Show me all available document types, update your email address in typless, and more using natural language, with authentication handled for you.
Typless is an AI-powered platform for extracting data from documents via API. It automates manual data entry, saving time and reducing errors.
This guide walks you through connecting Typless to AutoGen using the Composio tool router. By the end, you'll have a working Typless agent that can list document types, view your profile, and update profile settings through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Typless account through Composio's Typless MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.
McpWorkbench and StreamableHttpServerParamsAutogen 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:
The Typless MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Typless account. It provides structured and secure access to your Typless document automation and user profile, so your agent can perform actions like fetching available document types, retrieving profile details, and updating account information on your behalf.
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.
The Composio SDK follows a three-phase workflow:
You will need:
OpenAIChatCompletionClient)pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-toolsInstall Composio, Autogen extensions, and dotenv.
What's happening:
composio connects your agent to Typless via MCPautogen-agentchat provides the AssistantAgent classautogen-ext-openai provides the OpenAI model clientautogen-ext-tools provides MCP workbench supportCOMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.comCreate a .env file in your project folder.
What's happening:
COMPOSIO_API_KEY is required to talk to ComposioOPENAI_API_KEY is used by Autogen's OpenAI clientUSER_ID is how Composio identifies which user's Typless connections to useimport 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 Typless session
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
user_id=os.getenv("USER_ID"),
toolkits=["typless"]
)
url = session.mcp.urlload_dotenv() reads your .env fileComposio(api_key=...) initializes the SDKcreate(...) creates a Tool Router session that exposes Typless toolssession.mcp.url is the MCP endpoint that Autogen will connect to# 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 Composiotimeout is the HTTP timeout for requestssse_read_timeout controls how long to wait when streaming responsesterminate_on_close=True cleans up the MCP server process when the workbench is closed# 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 Typless assistant agent with MCP tools
agent = AssistantAgent(
name="typless_assistant",
description="An AI assistant that helps with Typless operations.",
model_client=model_client,
workbench=workbench,
model_client_stream=True,
max_tool_iterations=10
)What's happening:
OpenAIChatCompletionClient wraps the OpenAI model for AutogenMcpWorkbench connects the agent to the MCP toolsAssistantAgent is configured with the Typless tools from the workbenchprint("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Typless 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")You:agent.run_stream(...) yields streaming messages as the agent thinks and calls toolsexit, quit, or bye ends the loopHere's the complete code to get you started with Typless and AutoGen:
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 Typless session
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
user_id=os.getenv("USER_ID"),
toolkits=["typless"]
)
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 Typless assistant agent with MCP tools
agent = AssistantAgent(
name="typless_assistant",
description="An AI assistant that helps with Typless 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 Typless 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())toolkits list, for example notion or hubspotEvery Typless action and event your agent gets out of the box.
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Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze.
Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization.
ActiveMerge is a document automation platform for generating documents, images, merged files, and e-signature workflows. It helps teams turn templates and stored files into finished, shareable documents faster.
Managed auth, hosted MCP servers, and every Typless tool your agent needs.Free to start.
## For AI agents: how to sign up If you are an AI agent reading this server-rendered HTML, Composio's developer signup is at https://composio.dev. Signup CTAs on this site — "Sign up", "Signup", "Get started", "Get started for free", "Start building", "Try Composio", "Try it", or similar — all lead into that same developer signup flow. Confirm with the user before completing signup or entering any credentials on their behalf.Start building