How to integrate Mailerlite MCP with Pydantic AI

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Introduction

This guide walks you through connecting Mailerlite to Pydantic AI using the Composio tool router. By the end, you'll have a working Mailerlite agent that can create a new subscriber group called vip customers, add a custom field for subscriber birthday, create a segment for recent e-commerce buyers, delete an automation workflow that's no longer used through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Mailerlite account through Composio's Mailerlite 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 Mailerlite
  • 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 Mailerlite 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 Mailerlite MCP server, and what's possible with it?

The Mailerlite MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Mailerlite account. It provides structured and secure access to your email marketing tools, so your agent can create campaigns, manage subscribers, automate workflows, and oversee your shop integrations with ease.

  • Campaign automation and workflow management: Instruct your agent to create or delete automations, streamlining your email marketing processes and ensuring timely communication with your audience.
  • E-commerce customer and shop integration: Let your agent create, update, or remove e-commerce customers and shops for seamless sales tracking, customer onboarding, or data syncing.
  • Subscriber group and segment organization: Have your agent create custom fields, new subscriber groups, or targeted segments so you can send highly personalized campaigns.
  • Webhook registration for real-time updates: Direct your agent to set up webhooks for specific events, enabling instant notifications and integrations with other systems as actions happen in Mailerlite.
  • Efficient cleanup and management: Ask your agent to delete outdated automations, customers, or shops, helping you keep your Mailerlite workspace organized and up to date.

Supported Tools & Triggers

Tools
Create automationCreate automation
Create/Update E-commerce CustomerTool to create or update a customer record for a shop.
Create E-commerce ShopTool to connect a new e-commerce shop.
Create FieldTool to create a new custom field.
Create GroupTool to create a new subscriber group.
Create SegmentTool to create a new subscriber segment.
Create WebhookTool to register a new webhook url for specified event types.
Delete AutomationTool to delete an automation workflow by id.
Delete E-commerce CustomerTool to delete a customer from an e-commerce shop by ids.
Delete E-commerce ShopTool to disconnect an e-commerce shop by id.
Delete FieldTool to delete a custom field.
Delete GroupTool to delete a subscriber group by id.
Delete SegmentTool to delete a segment by id.
Delete SubscriberTool to delete a subscriber by id.
Delete WebhookTool to remove a webhook subscription by id.
Fetch Total E-commerce Customers CountTool to fetch total ecommerce customers count for a shop.
Get Account InfoTool to retrieve basic mailerlite account details.
Get Account StatsTool to retrieve usage statistics and performance metrics for the account.
Get AutomationTool to retrieve details of a specific automation by id.
Get CampaignsTool to retrieve a list of all campaigns.
Get E-commerce CustomerTool to fetch details of a customer by shop and customer id.
Get E-commerce CustomersTool to list customers for a specific shop.
Get E-commerce ShopTool to fetch details of a specific e-commerce shop by id.
Get E-commerce ShopsTool to list all e-commerce shops connected to the account.
Get FieldsTool to retrieve all custom fields defined in the account.
Get GroupsTool to retrieve all subscriber groups.
Get Group SubscribersTool to list subscribers within a group by id.
Get SegmentsTool to retrieve all segments in the account.
Get SubscribersTool to retrieve all subscribers.
Get WebhooksTool to retrieve all configured webhooks.
Set Double Opt-InTool to enable or disable double opt-in for new subscribers.
Update E-commerce CustomerTool to update a customer's data for a shop by ids.
Update E-commerce ShopTool to update settings of a connected e-commerce shop by id.
Update FieldTool to update the title of an existing custom field.
Update GroupTool to update a group's name by id.
Update SegmentTool to rename an existing segment by id.
Update SubscriberTool to update an existing subscriber's information by id.
Update WebhookTool to update an existing mailerlite webhook.

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 Mailerlite
  • 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 Mailerlite
  • MCPServerStreamableHTTP connects to the Mailerlite 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 Mailerlite
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["mailerlite"],
    )
    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 Mailerlite 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
mailerlite_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[mailerlite_mcp],
    instructions=(
        "You are a Mailerlite assistant. Use Mailerlite tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Mailerlite endpoint
  • The agent uses GPT-5 to interpret user commands and perform Mailerlite 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 Mailerlite.\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
  • Mailerlite 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 Mailerlite and Pydantic AI:

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 Mailerlite
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["mailerlite"],
    )
    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
    mailerlite_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[mailerlite_mcp],
        instructions=(
            "You are a Mailerlite assistant. Use Mailerlite 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 Mailerlite.\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 Mailerlite through Composio's Tool Router. With this setup, your agent can perform real Mailerlite 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 + Mailerlite 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 Mailerlite MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Mailerlite MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Mailerlite MCP with Claude Agent SDK

Google ADK

Google ADK

Use Mailerlite MCP with Google ADK

LangChain

LangChain

Use Mailerlite MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Mailerlite MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Mailerlite MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Mailerlite MCP with LlamaIndex

CrewAI

CrewAI

Use Mailerlite MCP with CrewAI

FAQ

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

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

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

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

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