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How to integrate Mailsoftly MCP with Pydantic AI

Connect Pydantic AI to Mailsoftly MCP. Verify if your mailsoftly api key is valid, check our company profile details on mailsoftly, and more using natural language, with authentication handled for you.

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Mailsoftly is an intuitive email marketing platform for businesses to create, schedule, and manage campaigns. It makes audience communication easy with automation and user-friendly tools.

20 Tools

Introduction

This guide walks you through connecting Mailsoftly to Pydantic AI using the Composio tool router. By the end, you'll have a working Mailsoftly agent that can manage contacts and lists, tag contacts, create email drafts, send emails, and check delivery status through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Mailsoftly account through Composio's Mailsoftly MCP server.

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

For exact tool slugs and parameter tables, see the tool catalog in the Composio docs.

Also integrate Mailsoftly with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIAutoGen

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 Mailsoftly
  • 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 Mailsoftly 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 Mailsoftly MCP server, and what's possible with it?

The Mailsoftly MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Mailsoftly account. It provides structured and secure access to your email marketing platform, so your agent can validate credentials, access firm information, and streamline campaign setup for you.

  • API key authentication validation: Have your agent confirm your API key is working and securely connected before taking further actions.
  • Retrieve firm details: Instantly pull details about your Mailsoftly organization to verify account information or tailor campaign strategies.
  • Credential troubleshooting automation: Let your agent proactively diagnose and report authentication issues, making onboarding and integration smoother.
  • Foundational checks for workflow automation: Use the agent to verify Mailsoftly connection status as the first step in building automated campaign flows.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

Step by step09 STEPS
1

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
2

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.
3

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 Mailsoftly
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

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
5

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 Mailsoftly
  • MCPServerStreamableHTTP connects to the Mailsoftly MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

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 Mailsoftly
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["mailsoftly"],
    )
    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 Mailsoftly 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
mailsoftly_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[mailsoftly_mcp],
    instructions=(
        "You are a Mailsoftly assistant. Use Mailsoftly tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Mailsoftly endpoint
  • The agent uses GPT-5 to interpret user commands and perform Mailsoftly operations
  • The instructions field defines the agent's role and behavior
8

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 Mailsoftly.\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
  • Mailsoftly API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

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 Mailsoftly 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 Mailsoftly
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["mailsoftly"],
    )
    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
    mailsoftly_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[mailsoftly_mcp],
        instructions=(
            "You are a Mailsoftly assistant. Use Mailsoftly 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 Mailsoftly.\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 Mailsoftly through Composio's Tool Router. With this setup, your agent can perform real Mailsoftly 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 + Mailsoftly for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every Mailsoftly action and event your agent gets out of the box.

Add Contact to Contact List

Tool to add an existing contact to a specific contact list.

Add Custom Field to Contact

Tool to add a custom field value to an existing contact.

Assign Tags to Contact

Tool to assign multiple tags to an existing contact at once.

Authenticate Firm

Tool to validate the API key and retrieve firm details.

Create Contact

Tool to create a new contact for the authenticated firm with email, first name, and last name.

Create Contact List

Tool to create a new contact list for the authenticated firm.

Create Email Drafts

Tool to create one or more email drafts in Mailsoftly.

Create or Update Contact

Tool to create a new contact or update an existing contact in Mailsoftly.

Get Contact

Retrieve a Mailsoftly contact by ID, returning its ID, email, first name and last name.

Get Contact Fields

Tool to fetch all contact fields available for a firm, excluding hidden columns.

Get Contact List

Tool to retrieve details of a specific contact list by ID.

Get Contact List Contacts

Tool to retrieve all contacts within a specific contact list.

Get Contact Lists

Tool to retrieve all contact lists for the authenticated firm.

Get Contacts

Tool to retrieve all contacts associated with a firm.

Get Custom Fields

Tool to retrieve all custom fields defined for the authenticated firm.

Get Email Status

Tool to fetch the status of a specific email draft by its ID.

Get Tags

Tool to retrieve all tags associated with the authenticated firm.

Search Contacts

Tool to search for contacts matching specified criteria in Mailsoftly.

Send Email

Tool to send an existing email draft that is marked as ready.

Update Contact

Tool to update an existing contact's information in Mailsoftly.

FRAMEWORKS

How to build Mailsoftly MCP Agent with another framework

Claude Code logo

Claude Code

Use Mailsoftly MCP with Claude Code

Claude Cowork logo

Claude Cowork

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OpenAI Agents SDK logo

OpenAI Agents SDK

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Claude Agent SDK logo

Claude Agent SDK

Use Mailsoftly MCP with Claude Agent SDK

Codex logo

Codex

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OpenClaw logo

OpenClaw

Use Mailsoftly MCP with OpenClaw

Hermes logo

Hermes

Use Mailsoftly MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Mailsoftly MCP with Atomic Agent

Google ADK logo

Google ADK

Use Mailsoftly MCP with Google ADK

LangChain logo

LangChain

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Vercel AI SDK logo

Vercel AI SDK

Use Mailsoftly MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Mailsoftly MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Mailsoftly MCP with LlamaIndex

CrewAI logo

CrewAI

Use Mailsoftly MCP with CrewAI

AutoGen logo

AutoGen

Use Mailsoftly MCP with AutoGen

FAQ

Frequently asked questions

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