How to integrate Bigmailer MCP with LangChain

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Introduction

This guide walks you through connecting Bigmailer to LangChain 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 LangChain 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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Bigmailer project to Composio
  • Create a Tool Router MCP session for Bigmailer
  • Initialize an MCP client and retrieve Bigmailer tools
  • Build a LangChain agent that can interact with Bigmailer
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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.

Supported Tools & Triggers

Tools
Create BrandTool to create a new brand in BigMailer.
Create Brand PropertyTool to create a brand property in BigMailer.
Create Bulk CampaignTool to create a bulk email campaign in BigMailer.
Create ContactTool to create a new contact in BigMailer within a specified brand.
Create Contact BatchTool to create a batch of contacts in BigMailer for a specific brand.
Create FieldTool to create a custom field in a BigMailer brand.
Create ListCreates a new contact list within a specified brand in BigMailer.
Create SegmentTool to create a segment in BigMailer for a specific brand.
Create Suppression ListTool to upload a suppression list for a brand in BigMailer.
Create TemplateTool to create a new email or page template in BigMailer.
Create Transactional CampaignCreates a new transactional campaign within a specified brand in BigMailer.
Create UserTool to create a new user in BigMailer.
Delete Brand PropertyTool to delete a brand property from a brand in BigMailer.
Delete ContactTool to delete a contact from a brand in BigMailer.
Delete Custom FieldDeletes a custom field from a specified brand in BigMailer.
Delete ListTool to delete a list from BigMailer.
Delete SegmentTool to delete a segment from a brand in BigMailer.
Delete TemplateTool to delete a template from BigMailer.
Delete UserTool to delete a user from BigMailer.
Get BrandTool to retrieve detailed information about a specific brand by its ID.
Get Brand PropertyTool to retrieve a specific brand property by its ID for a given brand.
Get Bulk CampaignTool to retrieve detailed information about a specific bulk campaign in BigMailer.
Get ContactTool to retrieve detailed information about a specific contact from BigMailer.
Get Contact Batch StatusTool to retrieve the status and results of a contact batch upload in BigMailer.
Get Custom FieldTool to retrieve a custom field from a BigMailer brand.
Get ListTool to retrieve details of a specific list within a brand.
Get SegmentTool to retrieve a specific segment from BigMailer by brand ID and segment ID.
Get Suppression ListTool to retrieve details of a specific suppression list for a brand in BigMailer.
Get TemplateTool to retrieve detailed information about a specific template by its ID.
Get Transactional CampaignTool to retrieve detailed information about a specific transactional campaign in BigMailer.
Get UserTool to retrieve detailed information about a specific user by their ID.
Get User InformationThis tool retrieves information about the authenticated user in BigMailer using the GET /me endpoint.
List All BrandsThis tool retrieves a list of all brands associated with the authenticated BigMailer account.
List Brand PropertiesTool to retrieve a list of brand properties for a specific brand in BigMailer.
List Bulk CampaignsTool to list bulk campaigns for a specified brand in BigMailer.
List ConnectionsTool to list all connections in your BigMailer account.
List ContactsTool to list contacts for a brand in BigMailer.
List FieldsTool to list custom fields for a brand in BigMailer.
List Contact ListsTool to retrieve all contact lists for a specified brand in BigMailer.
List Message TypesTool to list message types for a specific brand in BigMailer.
List SegmentsTool to list segments for a brand in BigMailer.
List SendersTool to list all senders configured for a specific brand in BigMailer.
List Suppression ListsTool to list suppression lists for a specific brand.
List TemplatesTool to list templates for a brand in BigMailer.
List Transactional CampaignsTool to list transactional campaigns for a specified brand in BigMailer.
List UsersTool to list all users in your BigMailer account.
Update BrandTool to update a brand in BigMailer.
Update Brand PropertyTool to update a brand property in BigMailer.
Update Bulk CampaignTool to update an existing bulk campaign in BigMailer.
Update ContactTool to update an existing contact in BigMailer.
Update FieldTool to update a custom field in BigMailer.
Update ListTool to update a list in BigMailer.
Update SegmentTool to update an existing segment in BigMailer.
Update TemplateTool to update an existing email or page template in BigMailer.
Update Transactional CampaignTool to update a transactional campaign in BigMailer.
Update UserTool to update a user in BigMailer.
Upsert ContactTool to create or update a contact in a BigMailer brand.

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

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI 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

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Bigmailer functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Bigmailer tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Bigmailer
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['bigmailer']
)

url = session.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
  • This approach allows the agent to dynamically load and use Bigmailer tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "bigmailer-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Bigmailer MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Bigmailer tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Bigmailer related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Bigmailer and LangChain:

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['bigmailer']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "bigmailer-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Bigmailer related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

Conclusion

You've successfully built a LangChain agent that can interact with Bigmailer through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

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FAQ

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

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.

Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain 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.

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

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.

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 Bigmailer data and credentials are handled as safely as possible.

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