How to integrate Reply io MCP with Autogen

This guide walks you through connecting Reply io to AutoGen using the Composio tool router. By the end, you'll have a working Reply io agent that can list all active campaigns this week, show contacts added to sales lists, delete a campaign by campaign id through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Reply io account through Composio's Reply io MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Reply.io is an AI-powered sales engagement platform for automating sales outreach across multiple channels. Boosts lead conversion and sales productivity through integrated workflows.

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Introduction

This guide walks you through connecting Reply io to AutoGen using the Composio tool router. By the end, you'll have a working Reply io agent that can list all active campaigns this week, show contacts added to sales lists, delete a campaign by campaign id through natural language commands.

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

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

Also integrate Reply io with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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

The Reply io MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Reply io account. It provides structured and secure access to your sales engagement platform, so your agent can manage campaigns, handle contacts, organize sequences, and automate routine sales operations on your behalf.

  • Campaign and sequence management: Effortlessly list, browse, and delete campaigns or sequences to keep your outreach organized and up to date.
  • Contact and list organization: Let your agent fetch, review, and organize your Reply io contacts and contact lists for targeted sales actions.
  • Email account administration: Retrieve all connected email accounts or remove outdated ones, making sure your sales tools stay streamlined.
  • User and access control: Easily remove users or generate unique identifiers for tasks, maintaining security and clarity in your team’s workflow.
  • Automated data retrieval: Quickly pull up paginated lists of campaigns, sequences, email accounts, or contact lists to inform your sales strategies and next steps.

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

Supported Tools

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

Add Contact to Sequence

Move an existing contact to a sequence in Reply.

Archive Sequence

Tool to archive a sequence.

Clear Contact Status

Tool to clear statuses from contacts.

Connect Exchange Account via OAuth

Tool to initiate OAuth connection for an Exchange email account.

Connect Gmail Account

Tool to initiate Gmail account connection via OAuth.

Create Contact

Tool to create a new contact in Reply.

Create Sequence Step

Tool to add a new step to an existing sequence.

Delete Contact

Tool to delete a contact.

Delete Email Account

Tool to delete a specific email account.

Delete Schedule

Tool to delete a schedule.

Delete Sequence

Tool to delete a sequence.

Delete User

Tool to delete a user.

Generate ULID

Generate ULID

Get Contact by ID

Tool to retrieve a contact by ID.

Get Contact Status

Tool to get contact status.

Get Current User

Tool to get the current authenticated user's ID.

Reply.io Get Disconnected Email Accounts

Tool to list email accounts that are currently disconnected due to authentication or connection errors.

Get Sequence By ID

Tool to retrieve detailed information about a sequence by its ID.

Get Sequence Contacts Extended

Tool to retrieve all contacts enrolled in a sequence with additional details.

Get Sequence Step by ID

Tool to retrieve details of a specific sequence step.

List Contacts Basic

Tool to list contacts.

Reply.io List Email Accounts

Tool to list all email accounts.

Reply.io List Lists

Tool to list all contact lists.

List Sequences

Tool to retrieve a paginated list of sequences.

List Sequence Steps

Tool to retrieve all steps in a sequence.

Pause Sequence

Tool to pause a running sequence.

Remove Contact From Sequence

Tool to remove a contact from a sequence.

Bulk Remove Contacts from Sequence

Tool to bulk remove multiple contacts from a sequence at once.

Search Contacts by Email

Tool to search contacts by email.

Set Contact Status

Tool to set the status of one or more contacts.

Start Sequence

Tool to start a sequence.

Update Contact

Tool to update an existing contact's information.

Update Email Account

Tool to update an existing email account with custom SMTP/IMAP settings.

FRAMEWORKS

How to build Reply io MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Reply io MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Reply io MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Reply io MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Reply io MCP with Claude Cowork

Codex logo

Codex

Use Reply io MCP with Codex

OpenClaw logo

OpenClaw

Use Reply io MCP with OpenClaw

Hermes logo

Hermes

Use Reply io MCP with Hermes

CLI logo

CLI

Use Reply io MCP with CLI

Google ADK logo

Google ADK

Use Reply io MCP with Google ADK

LangChain logo

LangChain

Use Reply io MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Reply io MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Reply io MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Reply io MCP with LlamaIndex

CrewAI logo

CrewAI

Use Reply io MCP with CrewAI

FAQ

Frequently asked questions

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

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

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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