How to integrate Bigmailer MCP with Pydantic AI

This guide walks you through connecting Bigmailer to Pydantic AI using the Composio tool router. By the end, you'll have a working Bigmailer agent that can create a new welcome campaign for brand x, list all brands i manage in bigmailer, get your bigmailer account user details through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Bigmailer account through Composio's Bigmailer MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES.

57 Tools

Introduction

This guide walks you through connecting Bigmailer to Pydantic AI using the Composio tool router. By the end, you'll have a working Bigmailer agent that can create a new welcome campaign for brand x, list all brands i manage in bigmailer, get your bigmailer account user details through natural language commands.

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

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

Also integrate Bigmailer with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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

The Bigmailer MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bigmailer account. It provides structured and secure access to your email marketing platform, so your agent can perform actions like creating transactional campaigns, retrieving your brands, and managing user account details on your behalf.

  • Automated transactional campaign creation: Have your agent quickly set up new transactional email campaigns for any of your brands, with full control over content, sender details, and subject lines.
  • Brand management and discovery: Let your agent list and organize all brands associated with your Bigmailer account, providing a clear overview for multi-brand operations.
  • User account information retrieval: Easily check your authenticated user details to verify API connectivity and view essential account information in real time.
  • Multi-brand marketing workflow automation: Empower your agent to streamline campaign launches and brand management across multiple business entities from one place.

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

Create Brand

Tool to create a new brand in BigMailer.

Create Brand Property

Tool to create a brand property in BigMailer.

Create Bulk Campaign

Tool to create a bulk email campaign in BigMailer.

Create Contact

Tool to create a new contact in BigMailer within a specified brand.

Create Contact Batch

Tool to create a batch of contacts in BigMailer for a specific brand.

Create Field

Tool to create a custom field in a BigMailer brand.

Create List

Creates a new contact list within a specified brand in BigMailer.

Create Segment

Tool to create a segment in BigMailer for a specific brand.

Create Suppression List

Tool to upload a suppression list for a brand in BigMailer.

Create Template

Tool to create a new email or page template in BigMailer.

Create Transactional Campaign

Creates a new transactional campaign within a specified brand in BigMailer.

Create User

Tool to create a new user in BigMailer.

Delete Brand Property

Tool to delete a brand property from a brand in BigMailer.

Delete Contact

Tool to delete a contact from a brand in BigMailer.

Delete Custom Field

Deletes a custom field from a specified brand in BigMailer.

Delete List

Tool to delete a list from BigMailer.

Delete Segment

Tool to delete a segment from a brand in BigMailer.

Delete Template

Tool to delete a template from BigMailer.

Delete User

Tool to delete a user from BigMailer.

Get Brand

Tool to retrieve detailed information about a specific brand by its ID.

Get Brand Property

Tool to retrieve a specific brand property by its ID for a given brand.

Get Bulk Campaign

Tool to retrieve detailed information about a specific bulk campaign in BigMailer.

Get Contact

Tool to retrieve detailed information about a specific contact from BigMailer.

Get Contact Batch Status

Tool to retrieve the status and results of a contact batch upload in BigMailer.

Get Custom Field

Tool to retrieve a custom field from a BigMailer brand.

Get List

Tool to retrieve details of a specific list within a brand.

Get Segment

Tool to retrieve a specific segment from BigMailer by brand ID and segment ID.

Get Suppression List

Tool to retrieve details of a specific suppression list for a brand in BigMailer.

Get Template

Tool to retrieve detailed information about a specific template by its ID.

Get Transactional Campaign

Tool to retrieve detailed information about a specific transactional campaign in BigMailer.

Get User

Tool to retrieve detailed information about a specific user by their ID.

Get User Information

This tool retrieves information about the authenticated user in BigMailer using the GET /me endpoint.

List All Brands

This tool retrieves a list of all brands associated with the authenticated BigMailer account.

List Brand Properties

Tool to retrieve a list of brand properties for a specific brand in BigMailer.

List Bulk Campaigns

Tool to list bulk campaigns for a specified brand in BigMailer.

List Connections

Tool to list all connections in your BigMailer account.

List Contacts

Tool to list contacts for a brand in BigMailer.

List Fields

Tool to list custom fields for a brand in BigMailer.

List Contact Lists

Tool to retrieve all contact lists for a specified brand in BigMailer.

List Message Types

Tool to list message types for a specific brand in BigMailer.

List Segments

Tool to list segments for a brand in BigMailer.

List Senders

Tool to list all senders configured for a specific brand in BigMailer.

List Suppression Lists

Tool to list suppression lists for a specific brand.

List Templates

Tool to list templates for a brand in BigMailer.

List Transactional Campaigns

Tool to list transactional campaigns for a specified brand in BigMailer.

List Users

Tool to list all users in your BigMailer account.

Update Brand

Tool to update a brand in BigMailer.

Update Brand Property

Tool to update a brand property in BigMailer.

Update Bulk Campaign

Tool to update an existing bulk campaign in BigMailer.

Update Contact

Tool to update an existing contact in BigMailer.

Update Field

Tool to update a custom field in BigMailer.

Update List

Tool to update a list in BigMailer.

Update Segment

Tool to update an existing segment in BigMailer.

Update Template

Tool to update an existing email or page template in BigMailer.

Update Transactional Campaign

Tool to update a transactional campaign in BigMailer.

Update User

Tool to update a user in BigMailer.

Upsert Contact

Tool to create or update a contact in a BigMailer brand.

FRAMEWORKS

How to build Bigmailer MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Bigmailer MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Bigmailer MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Bigmailer MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Bigmailer MCP with Claude Cowork

Codex logo

Codex

Use Bigmailer MCP with Codex

OpenClaw logo

OpenClaw

Use Bigmailer MCP with OpenClaw

Hermes logo

Hermes

Use Bigmailer MCP with Hermes

CLI logo

CLI

Use Bigmailer MCP with CLI

Google ADK logo

Google ADK

Use Bigmailer MCP with Google ADK

LangChain logo

LangChain

Use Bigmailer MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Bigmailer MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Bigmailer MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Bigmailer MCP with LlamaIndex

CrewAI logo

CrewAI

Use Bigmailer MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Bigmailer MCP server, the agents and LLMs can only access a fixed set of Bigmailer tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Bigmailer and many other apps based on the task at hand, all through a single MCP endpoint.

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 Bigmailer tools.

Yes, absolutely. You can configure which Bigmailer 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.

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 Bigmailer data and credentials are handled as safely as possible.

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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Jerome Leclanche
Co-Founder, Ingram Technologies