How to integrate Smartlead MCP with LangChain

This guide walks you through connecting Smartlead to LangChain using the Composio tool router. By the end, you'll have a working Smartlead agent that can list your campaigns, create draft campaigns, check delivery tests, and review email accounts through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Smartlead account through Composio's Smartlead MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Smartlead is a sales engagement platform for cold email campaigns, leads, sending accounts, inbox activity, deliverability, prospecting, and sender provisioning. Use it to run outbound sales at scale while keeping campaign operations, replies, and sender health in one place.

19 Tools

Introduction

This guide walks you through connecting Smartlead to LangChain using the Composio tool router. By the end, you'll have a working Smartlead agent that can list your campaigns, create draft campaigns, check delivery tests, and review email accounts through natural language commands.

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

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

Also integrate Smartlead with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Smartlead project to Composio
  • Create a Tool Router MCP session for Smartlead
  • Initialize an MCP client and retrieve Smartlead tools
  • Build a LangChain agent that can interact with Smartlead
  • 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 Smartlead MCP server, and what's possible with it?

The Smartlead MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Smartlead account. It provides structured and secure access to your campaigns, leads, inbox replies, sending accounts, deliverability tests, and prospecting tools, so your agent can manage campaigns, review performance, monitor replies, find prospects, and assess sender resources on your behalf.

  • Campaign creation and management: Have your agent create draft campaigns, review existing campaigns and their settings, or delete campaigns you no longer need.
  • Lead and performance monitoring: Let the agent list campaign leads, review email engagement statistics, remove unwanted leads, and resume paused leads.
  • Inbox and direct email actions: Instruct your agent to review lead replies across campaigns or send a single email from a connected Smartlead sending account.
  • Deliverability and account checks: Direct your agent to inspect sending account health, review spam and inbox placement tests, and organize tests with delivery folders.
  • Prospecting and sender research: Have your agent search prospect contacts, explore industries and saved searches, check prospect usage, compare sender vendors, and find available or purchased domains.

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 step10 STEPS
1

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
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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters 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/core is the core agent framework
  • dotenv/config loads environment variables
4

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
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Smartlead functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
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 Smartlead tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['smartlead']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Smartlead 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 Smartlead tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "smartlead-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Smartlead MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Smartlead tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

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

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept 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 invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

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

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['smartlead']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "smartlead-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Smartlead related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Smartlead 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.
TOOLS

Supported Tools

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

Create Draft Campaign

Create a new campaign in DRAFTED status.

Create Smart Delivery Folder

Create an organizational folder for Smart Delivery tests.

Delete Campaign

Permanently delete a campaign and all associated sequences, mappings, and statistics.

Delete Smart Delivery Folder

Delete an empty Smart Delivery folder.

Get Campaign

Get configuration and performance summary for one Smartlead campaign by ID.

Get Campaigns

Get configuration and performance summaries for 1-20 Smartlead campaigns.

Get Smart Delivery Test

Get the documented configuration for one Smart Delivery spam test by ID.

Get Smart Prospect Usage

Get Smart Prospect lead-search metrics, fetch counts, daily limits, and available credit balance.

List Campaigns

List campaigns visible to the connected Smartlead account, optionally for one client.

List Smart Delivery Folders

List folders used to organize Smart Delivery tests.

List Smart Delivery Tests

List Smart Delivery spam and inbox-placement tests.

List Email Accounts

List connected sending accounts with health, warmup, usage, provider, and campaign filters.

List Inbox Replies

List lead replies across campaigns from Master Inbox using bounded filters and one page at a time.

List Smart Prospect Industries

List and search Smart Prospect industry filter values without searching contacts or consuming contact-fetch credits.

List Purchased Smart Senders Domains

List domains already purchased through Smart Senders.

List Saved Smart Prospect Searches

List saved Smart Prospect search definitions without executing them or consuming contact-search credits.

List Smart Senders Vendors

List Smart Senders marketplace vendors and current domain/mailbox pricing without placing an order.

Search Available Smart Senders Domains

Check Smart Senders marketplace domain availability for a vendor.

Search Smart Prospect Contacts (Consumes Credits)

Search one page of Smart Prospect contacts.

FRAMEWORKS

How to build Smartlead MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Smartlead MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Smartlead MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Smartlead MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Smartlead MCP with Claude Cowork

Codex logo

Codex

Use Smartlead MCP with Codex

OpenClaw logo

OpenClaw

Use Smartlead MCP with OpenClaw

Hermes logo

Hermes

Use Smartlead MCP with Hermes

CLI logo

CLI

Use Smartlead MCP with CLI

Google ADK logo

Google ADK

Use Smartlead MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Smartlead MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Smartlead MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Smartlead MCP with LlamaIndex

CrewAI logo

CrewAI

Use Smartlead MCP with CrewAI

FAQ

Frequently asked questions

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

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 Smartlead tools.

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

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