How to integrate Quo MCP with Autogen

This guide walks you through connecting Quo to AutoGen using the Composio tool router. By the end, you'll have a working Quo agent that can get call details and voicemails, get messages, manage contacts, create tasks, and manage webhooks through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Quo account through Composio's Quo MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Quo logoQuo
Api Key

Quo is a business phone platform for calls, SMS, contacts, and team conversations. It helps teams manage customer communication from one shared, searchable workspace.

36 Tools

Introduction

This guide walks you through connecting Quo to AutoGen using the Composio tool router. By the end, you'll have a working Quo agent that can get call details and voicemails, get messages, manage contacts, create tasks, and manage webhooks through natural language commands.

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

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

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

The Quo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Quo account. It provides structured and secure access to your business calls, messages, contacts, conversations, tasks, users, and webhooks, so your agent can review calls, send text messages, manage contacts, organize conversations and tasks, and monitor webhook activity on your behalf.

  • Call and voicemail review: Have your agent review call participants, routing, status, timing, recordings, voicemail transcripts, and recording details.
  • Messaging and conversation management: Direct your agent to find and read messages, send texts from your Quo numbers, and mark conversations as read, open, or done.
  • Contact organization: Let the agent create, find, update, or delete contacts while working with standard details, custom fields, and external source information.
  • Task coordination: Instruct your agent to create and edit tasks, connect them to calls or conversations, assign teammates, set due dates, and complete or reopen work.
  • Webhook monitoring: Have your agent create, update, review, or remove webhook subscriptions and inspect their delivery activity and outcomes.

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

Supported Tools

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

Create Contact

Create a Quo contact with standard fields, optional custom fields, and external source metadata.

Create Task

Create a task linked to exactly one phone number, conversation, or activity.

Create Webhook

Create one unified webhook subscription for selected Quo events and return its signing secret, which must be stored securely.

Delete Contact

Permanently delete one Quo contact by ID.

Delete Task

Permanently delete one Quo task by ID.

Delete Webhook

Permanently delete one unified Quo webhook and revoke its signing secret.

Get Call

Get one call and its routing, participants, status, and timing details by ID.

Get Call Voicemail

Get voicemail processing status, transcript, duration, and recording URL for a Quo call.

Get Contact

Get one contact with default and custom fields by Quo contact ID.

Get Message

Get one message by Quo message ID, including its content, related IDs, participants, delivery status, and timestamps.

Get Phone Number

Get one Quo phone number and its assignments and restrictions by ID.

Get Task

Get one task and its current links, assignee, due date, and completion state.

Get User

Get one workspace user by Quo user ID.

Get Webhook

Get one unified Quo webhook by its numeric ID.

Get Webhook Delivery

Get the payload and attempt details for one Quo webhook delivery event.

List Call Recordings

List recording segments for a Quo call in chronological order.

List Calls

List calls between a Quo number and one external participant with optional user and creation-time filters.

List Contact Custom Fields

List the workspace's contact custom-field definitions for constructing valid contact values.

List Contacts

List contacts, optionally filtered by external IDs or source, with stable-v1 phone and custom fields.

List Conversations

List inbox conversations with optional phone-number, user, creation-time, update-time, and inactive-state filters.

List Messages

List messages exchanged by a Quo phone number and one or more participants, optionally filtered by sender or creation time.

List Phone Numbers

List Quo phone numbers and their assigned users, calling restrictions, and messaging restrictions.

List Tasks

List workspace tasks with cursor-controlled pagination.

List Users

List workspace users and return one cursor-controlled page.

List Webhook Deliveries

List one page of delivery events for a unified Quo webhook, optionally filtered by status, event type, or dispatch time.

List Webhooks

List unified Quo webhooks across call, message, contact, task, and integration event families.

Send Message

Send an irreversible text message from a Quo number to one or more recipients.

Send Message and Mark Conversation Done

Send an irreversible text message from a Quo number and move the resulting inbox conversation to Done.

Set Conversation Status

Set a Quo conversation to read, done, or open.

Set Task Assignee

Assign or unassign a Quo user on a task.

Set Task Completion

Complete or reopen a Quo task.

Set Task Conversation Link

Link or unlink a Quo task and conversation.

Set Task Due Date

Set or remove a Quo task's due date.

Update Contact

Patch selected standard, custom, or source fields on an existing Quo contact.

Update Task

Replace both the title and description of an existing Quo task.

Update Webhook

Partially update a unified Quo webhook.

FAQ

Frequently asked questions

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

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

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