How to integrate Mailcoach MCP with Pydantic AI

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Introduction

This guide walks you through connecting Mailcoach to Pydantic AI 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 Pydantic AI 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Mailcoach
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Mailcoach workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 with an active 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

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Mailcoach
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file

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

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Mailcoach
  • MCPServerStreamableHTTP connects to the Mailcoach MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Mailcoach
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["mailcoach"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an 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

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
mailcoach_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[mailcoach_mcp],
    instructions=(
        "You are a Mailcoach assistant. Use Mailcoach tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Mailcoach endpoint
  • The agent uses GPT-5 to interpret user commands and perform Mailcoach operations
  • The instructions field defines the agent's role and behavior

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Mailcoach.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Mailcoach API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Mailcoach
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["mailcoach"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    mailcoach_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[mailcoach_mcp],
        instructions=(
            "You are a Mailcoach assistant. Use Mailcoach tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Mailcoach.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

Conclusion

You've built a Pydantic AI agent that can interact with Mailcoach through Composio's Tool Router. With this setup, your agent can perform real Mailcoach actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Mailcoach for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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

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 Pydantic AI?

Yes, you can. Pydantic AI 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.

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