How to integrate Benchmark email MCP with LangChain

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Introduction

This guide walks you through connecting Benchmark email to LangChain using the Composio tool router. By the end, you'll have a working Benchmark email agent that can list all confirmed sender email addresses, get my benchmark account plan details, fetch company profile and contact limits, retrieve all current account settings through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Benchmark email account through Composio's Benchmark email 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:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Benchmark email project to Composio
  • Create a Tool Router MCP session for Benchmark email
  • Initialize an MCP client and retrieve Benchmark email tools
  • Build a LangChain agent that can interact with Benchmark email
  • 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 Benchmark email MCP server, and what's possible with it?

The Benchmark email MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Benchmark Email account. It provides structured and secure access to your email marketing data, so your agent can retrieve account info, manage contacts, handle lists, and automate campaign administration on your behalf.

  • Automated contact and list management: Effortlessly add, update, or delete contacts and lists, keeping your subscriber base organized and up to date.
  • Campaign cleanup and maintenance: Direct your agent to delete obsolete email campaigns or remove unneeded webhooks to keep your workspace tidy.
  • Account insights and configuration retrieval: Have the agent fetch client details, plan information, and account settings—perfect for reporting or reviewing your workspace setup.
  • Confirmed email address retrieval: Quickly pull all verified sender email addresses for compliance and seamless campaign sending.
  • Agency account and webhook control: Manage linked agency accounts and webhooks by deleting or updating them when no longer needed for more secure integrations.

Supported Tools & Triggers

Tools
Delete Contact From ListTool to delete a contact from a specific list by contactid.
Delete Contact ListTool to delete a contact list.
Delete Email CampaignTool to delete an email campaign.
Delete Linked Agency AccountTool to delete a linked agency account.
Delete WebhookTool to delete a webhook from a contact list by its id.
Get All Confirmed EmailsTool to retrieve all confirmed email addresses for the client account.
Get Client Account SettingsTool to get client account settings such as company, language, timezone, and sender info.
Get client detailsTool to get client details including profile data, contact count, and plan information.
Get Client Plan InformationTool to get client's plan information including addons, email plan, and total contacts.
Get client profile detailsTool to get client's profile details like business city, country, phone, and company.
Get Contact List DetailsTool to fetch detailed information for a contact list.
Get Contact ListsTool to retrieve all contact lists.
Get Filtered Contacts in ListTool to fetch filtered and paginated contacts from a list by listid.
Get Email Report ForwardsTool to get forwards report for an email campaign.
Get Unopens ReportTool to get unopens report for an email campaign by id.
Get Linked Agency Account DetailsTool to get details of a linked agency account.
Get Linked Agency AccountsTool to get list of linked agency accounts.
Get sub-account detailsTool to get details for a specific sub-account by id.
Get Sub-Account HistoryTool to get sub-account history.
Get Sub-AccountsTool to retrieve all sub-accounts for the client.
Get Sub-Accounts Plan ListTool to retrieve available plans for a sub-account.
Change PasswordTool to change the password for the client account.
Save Security PINTool to save a new security pin for the client account.
Send Reset EmailTool to send a reset email link to change the primary email address.
Patch Update Client SettingsTool to update client account settings.
Update Contact ListTool to update an existing contact list.
Update/Edit ProfileTool to update or edit profile information such as first name, last name, and phone number.
Update WebhookTool to update a webhook for a contact list by webhook id.
Add Contact to ListTool to add a new contact to a specific list.
Change Security PINTool to change security pin for the client account.
Create Contact ListTool to create a new contact list.
Create WebhookTool to create a new webhook for a contact list.
Disable Security PINTool to disable security pin for the client account.
Save Website DomainTool to save a website domain for your benchmark email account.
Send Confirm Email VerificationTool to send confirm email verification.
Send PIN via EmailTool to send pin via email.

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 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 Benchmark email 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 Benchmark email tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Benchmark email 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 Benchmark email tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "benchmark_email-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 Benchmark email MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Benchmark email 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 Benchmark email 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 Benchmark email 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=['benchmark_email']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "benchmark_email-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 Benchmark email 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 Benchmark email 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.

How to build Benchmark email MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Benchmark email MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Benchmark email MCP with Claude Agent SDK

Google ADK

Google ADK

Use Benchmark email MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Benchmark email MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Benchmark email MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Benchmark email MCP with LlamaIndex

CrewAI

CrewAI

Use Benchmark email MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Benchmark email MCP?

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

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

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

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