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How to integrate Deadline funnel MCP with Autogen

Connect Autogen to Deadline funnel MCP. Create a new deadline campaign for a product launch, list all active campaigns and their end dates, and more using natural language, with authentication handled for you.

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Deadline Funnel lets you create personalized deadlines and timers for your marketing campaigns. It helps marketers boost conversions by adding authentic urgency to offers.

6 Tools

Introduction

This guide walks you through connecting Deadline funnel to AutoGen using the Composio tool router. By the end, you'll have a working Deadline funnel agent that can start campaign deadlines, list your campaigns, track sales, and generate tracking webhooks through natural language commands.

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

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

Also integrate Deadline funnel with

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

The Deadline funnel MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Deadline Funnel account. It provides structured and secure access to your deadline campaigns, so your agent can automate deadline creation, manage campaign settings, personalize timers, and track conversions on your behalf.

  • Automated deadline campaign management: Enable your agent to create, update, or delete deadline funnels for your marketing campaigns to drive timely conversions.
  • Personalized timer setup: Let your agent set up unique countdown timers tailored to individual leads or segments, helping you boost urgency with authentic deadlines.
  • Campaign analytics monitoring: Have your agent fetch and summarize performance metrics like conversion rates and timer effectiveness for any campaign.
  • Trigger-based actions: Program your agent to initiate or modify deadlines based on user actions or campaign milestones, ensuring dynamic and responsive campaigns.
  • Multi-channel deadline integration: Allow your agent to synchronize deadlines across email, landing pages, and other marketing assets for a seamless, consistent user experience.

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

Supported Tools

Every Deadline funnel action and event your agent gets out of the box.

Email Link Redirect

Follows a Deadline Funnel email link for a subscriber and returns the resulting URL.

Generate Sales Tracking Webhook URL

Attempts to generate campaign-specific sales-tracking webhook parameters.

Get Account ID

Retrieves the Deadline Funnel account ID for use in subsequent API calls.

List Campaigns

Lists Deadline Funnel campaigns accessible to the authenticated account, providing campaign IDs and names for downstream actions.

Start Deadline via Custom Webhook

Posts a subscriber's email to a campaign-specific custom webhook to start deadline tracking.

Track Sale Webhook

Tool to record a sale for a subscriber in a specific campaign via the campaign-generated sales-tracking webhook.

FRAMEWORKS

How to build Deadline funnel MCP Agent with another framework

Claude Code logo

Claude Code

Use Deadline funnel MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Deadline funnel MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Deadline funnel MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Deadline funnel MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

Use Deadline funnel MCP with Grok Bot

Codex logo

Codex

Use Deadline funnel MCP with Codex

OpenClaw logo

OpenClaw

Use Deadline funnel MCP with OpenClaw

Hermes logo

Hermes

Use Deadline funnel MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Deadline funnel MCP with Atomic Agent

Google ADK logo

Google ADK

Use Deadline funnel MCP with Google ADK

LangChain logo

LangChain

Use Deadline funnel MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Deadline funnel MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Deadline funnel MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Deadline funnel MCP with LlamaIndex

CrewAI logo

CrewAI

Use Deadline funnel MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Deadline funnel MCP with Pydantic AI

FAQ

Frequently asked questions

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

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

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