How to integrate Mailcoach MCP with CrewAI

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Introduction

This guide walks you through connecting Mailcoach to CrewAI 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 CrewAI 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 a Composio API key and configure your Mailcoach connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Mailcoach
  • Build a conversational loop where your agent can execute Mailcoach operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Mailcoach connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Mailcoach via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_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 with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Mailcoach MCP URL

Create a Composio Tool Router session for Mailcoach

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["mailcoach"],
)
url = session.mcp.url
What's happening:
  • You create a Mailcoach only session through Composio
  • Composio returns an MCP HTTP URL that exposes Mailcoach tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Mailcoach Assistant",
    goal="Help users interact with Mailcoach through natural language commands",
    backstory=(
        "You are an expert assistant with access to Mailcoach tools. "
        "You can perform various Mailcoach operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Mailcoach MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Mailcoach operations.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Mailcoach related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_mailcoach_agent.py

Complete Code

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

python
# file: crewai_mailcoach_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Mailcoach session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["mailcoach"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Mailcoach assistant agent
    toolkit_agent = Agent(
        role="Mailcoach Assistant",
        goal="Help users interact with Mailcoach through natural language commands",
        backstory=(
            "You are an expert assistant with access to Mailcoach tools. "
            "You can perform various Mailcoach operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Mailcoach operations.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Mailcoach related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Mailcoach through Composio's Tool Router. The agent can perform Mailcoach operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

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

LangChain

LangChain

Use Mailcoach MCP with LangChain

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

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 CrewAI?

Yes, you can. CrewAI 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

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