How to integrate Lemlist MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Lemlist to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Lemlist agent that can export all leads from current campaign, download list of unsubscribed emails, unsubscribe specific lead from a campaign, check status of campaign export request through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Lemlist account through Composio's Lemlist MCP server.

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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Lemlist
  • Configure an AI agent that can use Lemlist as a tool
  • Run a live chat session where you can ask the agent to perform Lemlist operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the Lemlist MCP server, and what's possible with it?

The Lemlist MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Lemlist account. It provides structured and secure access to your outreach campaigns, so your agent can manage leads, automate campaign exports, monitor unsubscribe lists, and orchestrate multichannel engagement on your behalf.

  • Automated campaign management: Retrieve campaign details by ID, audit campaign sequences, and start or monitor campaign exports for streamlined reporting and analytics.
  • Lead and subscriber control: Unsubscribe leads from campaigns, delete unsubscribed emails, or export detailed lists of campaign leads to keep your outreach data fresh and compliant.
  • Outreach data exports: Initiate and track asynchronous exports of campaign statistics or download CSVs of unsubscribed contacts for deeper insights and record-keeping.
  • Webhook administration: Fetch all configured webhooks to sync Lemlist with your other tools or audit integration points for better workflow automation.
  • Schedule management: Permanently delete schedules you no longer need, ensuring your campaigns stay organized and up to date.

Supported Tools & Triggers

Tools
Delete ScheduleTool to delete a specific schedule by scheduleid.
Delete Unsubscribed EmailTool to delete an email from the unsubscribed list.
Unsubscribe Lead From CampaignTool to unsubscribe a lead from a campaign.
Get All WebhooksTool to retrieve the list of all webhooks configured for the team.
Get Campaign By IDTool to retrieve a specific campaign by campaignid.
Start Campaign ExportTool to start an asynchronous export of all campaign statistics (csv).
Get Campaign Export StatusTool to check the status of an asynchronous campaign export.
Get Campaign SequencesTool to retrieve a list of all sequences for a campaign with steps and conditions.
Export Campaign LeadsTool to export campaign leads with state filtering and choose between json or csv output.
Export UnsubscribesTool to download a csv file containing all unsubscribed email addresses.
Get Unsubscribed EmailTool to retrieve a single unsubscribed email record.
Retrieve ActivitiesTool to fetch recent campaign activities.
Retrieve Lead By EmailTool to retrieve a lead by their email address.
Retrieve UnsubscribesTool to retrieve the list of all people who are unsubscribed.
Get Team CreditsTool to retrieve credits left in the team.
Get Team InfoTool to retrieve information about your team.
Get User InfoTool to retrieve all information of the authenticated user.
Mark Lead as Not Interested in CampaignTool to mark a lead as not interested in a specific campaign.
Update CampaignTool to update settings of a campaign.
Update ScheduleTool to update an existing schedule with new parameters.
Add Unsubscribe Email/DomainTool to add an email or domain to the unsubscribed list.
Add Variables to LeadTool to add one or more variables to a lead.
Associate schedule with campaignTool to associate a schedule with a campaign.
Create CampaignTool to create a new campaign.
Create ScheduleTool to create a new schedule for the team.
Mark Lead As InterestedTool to mark a lead as interested in all campaigns.
Mark Lead As Interested In CampaignTool to mark a lead as interested in a specific campaign.
Mark Lead As Not InterestedTool to mark a lead as not interested in all campaigns.
Pause a running campaignTool to pause a running campaign.
Pause LeadTool to pause a lead in all campaigns or a specific campaign.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Lemlist project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Lemlist.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Lemlist Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["lemlist"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only lemlist.
  • The router checks the user's Lemlist connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Lemlist.
  • This approach keeps things lightweight and lets the agent request Lemlist tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Lemlist. "
        "Help users perform Lemlist operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Lemlist and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Lemlist operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Lemlist.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Lemlist and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["lemlist"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Lemlist. "
        "Help users perform Lemlist operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Lemlist MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Lemlist.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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FAQ

What are the differences in Tool Router MCP and Lemlist MCP?

With a standalone Lemlist MCP server, the agents and LLMs can only access a fixed set of Lemlist tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Lemlist and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Lemlist tools.

Can I manage the permissions and scopes for Lemlist while using Tool Router?

Yes, absolutely. You can configure which Lemlist 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.

How safe is my data with Composio Tool Router?

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 Lemlist data and credentials are handled as safely as possible.

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