How to integrate Unione MCP with Autogen

This guide walks you through connecting Unione to AutoGen using the Composio tool router. By the end, you'll have a working Unione agent that can check your current unione email balance, cancel a scheduled email by job id, list all sender domains and their status through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Unione account through Composio's Unione MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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UniOne is an email delivery service with a flexible Web API and SMTP API for transactional and marketing emails. It streamlines reliable, scalable email sending for developers and businesses.

32 Tools

Introduction

This guide walks you through connecting Unione to AutoGen using the Composio tool router. By the end, you'll have a working Unione agent that can check your current unione email balance, cancel a scheduled email by job id, list all sender domains and their status through natural language commands.

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

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

Also integrate Unione with

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

The Unione MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Unione account. It provides structured and secure access to your Unione email delivery service, so your agent can send transactional or marketing emails, manage sending domains, monitor delivery events, check account balance, and automate email operations on your behalf.

  • Automated email sending and scheduling: Have your agent send transactional or marketing emails and even schedule deliveries right from your Unione account.
  • Domain verification and management: Easily manage sender domains, trigger domain verifications, and handle DNS/DKIM checks to keep your emails deliverable.
  • Event monitoring and export: Let your agent fetch specific email events, retrieve delivery metrics, or export comprehensive email event logs for auditing and analytics.
  • Account balance and plan checks: Quickly access your current email balance and subscription plan details, ensuring you stay within your sending limits.
  • Email job and pricing insights: Retrieve detailed information about specific email jobs and get up-to-date pricing for cost management before sending campaigns.

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

Supported Tools

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

Delete Event Dump

Tool to delete an event dump file and remove it from the queue or storage.

Delete Template

Tool to delete a template by ID.

Delete Webhook

Tool to delete a webhook event notification handler by its URL.

UniOne Email Balance

Tool to retrieve current account balance.

Cancel Scheduled Email

Tool to cancel a scheduled transactional email by its job ID.

UniOne Email Domain Management

Tool to manage sender domains in UniOne.

Get Email Event

Tool to retrieve details of a specific email event by its ID.

Get Email Send Job

Tool to retrieve detailed information about a specific email send job.

UniOne Email List (Export)

Tool to export email events within a specified time frame.

Resend Sent Email

Tool to resend a previously sent email by its job ID.

UniOne Email Resubscribe

Tool to resubscribe a recipient who previously unsubscribed.

Resume Paused Email

Tool to resume a paused transactional email by its job ID.

UniOne Email SMTP Configuration

Tool to retrieve SMTP server details and credentials.

UniOne Email Statistics

Tool to retrieve email sending statistics over a specified time range.

UniOne Email Unsubscribe

Tool to unsubscribe an email from future emails.

Batch Email Validation

Tool to validate multiple email addresses in a batch.

Remove Email from Suppression List

Tool to remove an email from the suppression list.

Retry Email Validation

Tool to retry an email validation request.

UniOne Email Webhook Types

Tool to retrieve supported email webhook event types.

Create Event Dump

Tool to create an asynchronous CSV event dump.

UniOne Event Dump List

Tool to retrieve the full list of event dumps.

Get Event Dump

Tool to retrieve the status and download URLs of an event dump.

Get Email Suppression Details

Tool to check if an email is suppressed and retrieve the reason and date.

Get Template

Tool to get template properties by ID.

Get Webhook Configuration

Tool to retrieve webhook configuration by its URL.

Schedule Email

Tool to schedule a transactional email up to 24 hours ahead.

Suppression List

Tool to return the suppression list since a given date.

Delete Tag

Tool to delete a specific tag.

UniOne Tag List

Tool to retrieve all user-defined tags.

UniOne Template List

Tool to list email templates.

Set Template

Tool to set or update an email template.

Set Webhook

Tool to set or edit a webhook event notification handler.

FAQ

Frequently asked questions

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

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

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