How to integrate Mailcoach MCP with LangChain

BOOK A CALLGET STARTED FOR FREE
Framework Integration Gradient
Mailcoach Logo
LangChain Logo
divider

Introduction

This guide walks you through connecting Mailcoach to LangChain using the Composio tool router. By the end, you'll have a working Mailcoach agent that can create a new email campaign for product launch, add a subscriber to the weekly newsletter list, tag all subscribers interested in webinars, confirm a subscriber's double opt-in registration through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Mailcoach account through Composio's Mailcoach 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
  • Connect your Mailcoach project to Composio
  • Create a Tool Router MCP session for Mailcoach
  • Initialize an MCP client and retrieve Mailcoach tools
  • Build a LangChain agent that can interact with Mailcoach
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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

The Mailcoach MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Mailcoach account. It provides structured and secure access to your email marketing platform, so your agent can manage campaigns, organize subscriber lists, create templates, and automate email workflows on your behalf.

  • Email campaign creation and scheduling: Direct your agent to launch new campaigns, send emails to specific lists, or set up campaign schedules based on your marketing needs.
  • Subscriber list and segmentation management: Let your agent create new email lists, add or confirm subscribers, and apply tags for better audience segmentation and targeting.
  • Template management and customization: Instruct your agent to create, update, or organize reusable email templates and transactional templates for efficient campaign building.
  • Automated suppression and bounce handling: Have your agent add suppressions for bounced or blocked addresses, keeping your lists clean and compliant with deliverability best practices.
  • Bulk subscriber import and data enrichment: Enable your agent to import subscribers via CSV, append new data to existing imports, and streamline growth of your contact lists.

Supported Tools & Triggers

Tools
Add Mailcoach CampaignTool to create a new mailcoach campaign.
Add Email ListTool to create a new email list.
Add suppressionTool to add a suppression entry.
Add Tag to Email ListTool to create a new tag within a specific email list.
Add Tags to SubscriberTool to add tags to a subscriber.
Add TemplateTool to create a new email template.
Add Transactional Email TemplateTool to create a new template that can be used for transactional emails.
Append to Subscriber ImportTool to append csv data to an existing subscriber import.
Confirm SubscriberTool to confirm a subscriber’s subscription.
Create Subscriber ImportTool to create a new subscriber import.
Delete CampaignTool to delete a campaign by uuid.
Delete Email ListTool to delete an email list by uuid.
Delete SendTool to delete a sent item by its uuid.
Delete SubscriberTool to delete a subscriber by uuid.
Delete Subscriber ImportTool to delete a subscriber import by its uuid.
Delete SuppressionTool to delete a suppression entry by uuid.
Delete Tag from Email ListTool to delete a tag from an email list.
Delete TemplateTool to delete a template by uuid.
Delete Transactional MailTool to delete a transactional mail by its uuid.
Get All CampaignsTool to retrieve all campaigns.
Get All Sent ItemsTool to retrieve all sent items.
Get All Subscriber ImportsTool to retrieve all subscriber imports.
Get All SuppressionsTool to list all suppression entries.
Get All TagsTool to retrieve all tags for a specific email list.
Get All TemplatesTool to retrieve all templates.
Get All Transactional Email TemplatesTool to retrieve all transactional email templates.
Get Email ListsTool to retrieve all email lists.
Get Specific CampaignTool to retrieve details of a specific mailcoach campaign.
Get Specific Email ListTool to retrieve a specific email list.
Get Specific SubscriberTool to retrieve a specific subscriber.
Get Specific SuppressionTool to retrieve a specific suppression entry.
Get Specific TagTool to retrieve details of a specific tag.
Get Specific TemplateTool to retrieve details of a specific template.
Get Transactional MailsTool to retrieve all transactional mail templates.
Remove Tags from SubscriberTool to remove tags from a subscriber.
Resend Subscriber ConfirmationTool to resend confirmation email to a subscriber.
Start Subscriber ImportTool to start processing a subscriber import.
Subscribe To Email ListTool to add or update a subscriber in an email list.
Unsubscribe SubscriberTool to unsubscribe a subscriber from an email list.
Update CampaignTool to update an existing mailcoach campaign.
Update Email ListTool to update an existing email list.
Update SubscriberTool to update a subscriber.
Update Subscriber ImportTool to update an existing subscriber import.
Update TagTool to update an existing tag within an email list.
Update TemplateTool to update an existing template's name or content.

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 this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

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.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Mailcoach functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Mailcoach tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Mailcoach
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['mailcoach']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Mailcoach tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Mailcoach tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "mailcoach-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Mailcoach MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Mailcoach tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Mailcoach related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Mailcoach and LangChain:

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['mailcoach']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "mailcoach-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Mailcoach related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Mailcoach through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

How to build Mailcoach MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Mailcoach MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Mailcoach MCP with Claude Agent SDK

Google ADK

Google ADK

Use Mailcoach MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Mailcoach MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Mailcoach MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Mailcoach MCP with LlamaIndex

CrewAI

CrewAI

Use Mailcoach MCP with CrewAI

FAQ

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

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

Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain 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 Mailcoach tools.

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

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

Used by agents from

Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Book a call↗Get started for free