How to integrate Mailtrap MCP with Pydantic AI

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Introduction

This guide walks you through connecting Mailtrap to Pydantic AI using the Composio tool router. By the end, you'll have a working Mailtrap agent that can send a test email to marketing team, list all emails sent from mailtrap today, create a new inbox for transactional testing through natural language commands.

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

The Mailtrap MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Mailtrap account. It provides structured and secure access so your agent can perform Mailtrap operations on your behalf.

Supported Tools & Triggers

Tools
Clean InboxTool to clean an inbox in Mailtrap by deleting all messages.
Create ContactTool to create a new contact in Mailtrap.
Create Contact EventTool to create a contact event in Mailtrap.
Create Contact ExportTool to create a contact export job for a Mailtrap account.
Create Contact FieldTool to create a custom contact field in Mailtrap.
Create Contact ListTool to create a new contact list in Mailtrap.
Create Email TemplateTool to create a new email template in Mailtrap account.
Create Sending DomainTool to create a new sending domain in Mailtrap.
Delete ContactTool to delete a contact from a Mailtrap account.
Delete Contact FieldTool to delete a contact field by its ID.
Delete Contact ListTool to delete a contact list by its ID.
Delete Email TemplateTool to delete an email template from a Mailtrap account.
Delete ProjectTool to delete a project from Mailtrap.
Delete Sending DomainTool to delete a sending domain from a Mailtrap account.
Get Billing UsageTool to retrieve current billing cycle usage for an account.
Get ContactTool to retrieve a contact by UUID or email address from Mailtrap.
Get Contact ExportTool to retrieve the status of a contact export.
Get Contact FieldTool to retrieve contact field details by field ID.
Get Contact Import StatusTool to retrieve the status of a contact import operation.
Get Contact ListTool to retrieve a specific contact list by its ID.
Get Email TemplateTool to retrieve details of a specific email template by ID.
Get Inbox AttributesTool to retrieve inbox attributes from Mailtrap.
Get Message HTML BodyTool to retrieve the HTML body of a message from Mailtrap.
Get Permission ResourcesTool to retrieve all resources in account for permission management.
Get Project by IDTool to retrieve project details from Mailtrap by project ID.
Get Sending DomainTool to retrieve sending domain details from Mailtrap.
Get Sending StatsTool to retrieve email sending statistics from Mailtrap for a specific account.
Get Sending Stats by CategoriesTool to retrieve email sending statistics grouped by categories.
Get Sending Stats by DateTool to retrieve email sending statistics aggregated by date.
Get Sending Stats by DomainsTool to retrieve sending statistics grouped by domains for a Mailtrap account.
Get Sending Stats by ESPTool to retrieve email sending statistics grouped by email service providers (ESPs) for a specified date range.
Import ContactsTool to import contacts in bulk to Mailtrap.
List AccountsTool to list all Mailtrap accounts you have access to.
List Contact FieldsTool to get all contact fields for a Mailtrap account.
List Contact ListsTool to retrieve all contact lists for a Mailtrap account.
List Email TemplatesTool to retrieve all email templates for a Mailtrap account.
List InboxesTool to get a list of inboxes for a Mailtrap account.
List Messages in InboxTool to get messages from a Mailtrap inbox.
List ProjectsTool to get a list of projects for a Mailtrap account.
List Sending DomainsTool to list all sending domains for a Mailtrap account.
List Email SuppressionsTool to list suppressed email addresses for a Mailtrap account.
Mark Inbox as ReadTool to mark all messages in a Mailtrap inbox as read.
Reset Inbox CredentialsTool to reset SMTP credentials for a Mailtrap inbox.
Update contactTool to update an existing contact in Mailtrap.
Update Contact FieldTool to update a contact field in Mailtrap.
Update Contact ListTool to update a contact list's name in Mailtrap.
Update Email TemplateTool to update an existing email template in Mailtrap account.
Update inboxTool to update an inbox's settings in Mailtrap.
Update projectTool to update a project's name in Mailtrap.

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 Mailtrap
  • 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 Mailtrap
  • MCPServerStreamableHTTP connects to the Mailtrap 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 Mailtrap
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["mailtrap"],
    )
    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 Mailtrap 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
mailtrap_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[mailtrap_mcp],
    instructions=(
        "You are a Mailtrap assistant. Use Mailtrap tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Mailtrap endpoint
  • The agent uses GPT-5 to interpret user commands and perform Mailtrap 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 Mailtrap.\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
  • Mailtrap 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 Mailtrap 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 Mailtrap
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["mailtrap"],
    )
    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
    mailtrap_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[mailtrap_mcp],
        instructions=(
            "You are a Mailtrap assistant. Use Mailtrap 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 Mailtrap.\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 Mailtrap through Composio's Tool Router. With this setup, your agent can perform real Mailtrap 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 + Mailtrap 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 Mailtrap MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Mailtrap MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Mailtrap MCP with Claude Agent SDK

Google ADK

Google ADK

Use Mailtrap MCP with Google ADK

LangChain

LangChain

Use Mailtrap MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Mailtrap MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Mailtrap MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Mailtrap MCP with LlamaIndex

CrewAI

CrewAI

Use Mailtrap MCP with CrewAI

Claude Code

Claude Code

Use Mailtrap MCP with Claude Code

Codex

Codex

Use Mailtrap MCP with Codex

FAQ

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

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

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

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

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