How to integrate Sequenzy MCP with LangChain

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

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Sequenzy is an email marketing and automation platform for subscribers, campaigns, sequences, transactional email, analytics, and workspace resources. Use it to manage lifecycle email, audience growth, and performance tracking from one place.

10 Tools

Introduction

This guide walks you through connecting Sequenzy to LangChain using the Composio tool router. By the end, you'll have a working Sequenzy agent that can list your campaigns and sequences, browse subscribers, review email metrics, and manage tags through natural language commands.

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

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

Also integrate Sequenzy 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 Sequenzy project to Composio
  • Create a Tool Router MCP session for Sequenzy
  • Initialize an MCP client and retrieve Sequenzy tools
  • Build a LangChain agent that can interact with Sequenzy
  • 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 Sequenzy MCP server, and what's possible with it?

The Sequenzy MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Sequenzy account. It provides structured and secure access to your subscribers, campaigns, sequences, templates, tags, lists, and email metrics, so your agent can review audiences, inspect marketing activity, find reusable content, manage tags, and analyze email performance on your behalf.

  • Subscriber and audience review: Have your agent search subscribers, retrieve individual profiles with memberships and recent activity, and review the lists available for audience targeting.
  • Campaign and sequence discovery: Let the agent find campaigns by delivery status or label, then inspect sequences to see whether they accept new enrollments or process existing ones.
  • Email performance analysis: Instruct your agent to review delivery and engagement totals and rates for a recent period or custom date range, with optional filters for email type or mailbox provider.
  • Template discovery: Direct your agent to find reusable email templates and campaign email content by label, including available localization details.
  • Subscriber tag management: Have your agent list available tags, create normalized tag definitions, or delete non-system tags that are no longer needed.

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 Sequenzy 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 Sequenzy 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: ['sequenzy']
    }
);

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

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "sequenzy-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 Sequenzy MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Sequenzy 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 Sequenzy 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 Sequenzy 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: ['sequenzy']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "sequenzy-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 Sequenzy 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 Sequenzy 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 Sequenzy action and event your agent gets out of the box.

Create Tag

Create a reusable subscriber tag definition; Sequenzy normalizes its name to lowercase and replaces spaces with hyphens.

Delete Tag

Permanently delete a non-system tag definition and remove it from every subscriber.

Get Email Metrics

Return workspace-wide email delivery and engagement totals and rates for a sliding window or custom range, optionally filtered by email type or mailbox provider.

Get Subscriber

Retrieve one subscriber by email with list memberships, sequence enrollments, notes, engagement totals, and recent activity.

List Campaigns

Discover campaigns in the connected workspace, optionally filtered by delivery status or label, without scheduling or sending them.

List Sequences

Discover automation sequences and inspect whether they accept new enrollments or process existing ones, without activating or enrolling anyone.

List Subscriber Lists

Return the reusable subscriber lists available for audience filtering and membership workflows.

List Subscribers

Search and filter subscribers in the connected workspace, returning one stable cursor page for audience review or export.

List Tags

Return reusable subscriber tag definitions, including which tags are protected system tags.

List Templates

Discover reusable email templates and campaign-backed email bodies by label, returning one page with localization metadata.

FRAMEWORKS

How to build Sequenzy MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Sequenzy MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Sequenzy MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Sequenzy MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Sequenzy MCP with Claude Cowork

Codex logo

Codex

Use Sequenzy MCP with Codex

OpenClaw logo

OpenClaw

Use Sequenzy MCP with OpenClaw

Hermes logo

Hermes

Use Sequenzy MCP with Hermes

CLI logo

CLI

Use Sequenzy MCP with CLI

Google ADK logo

Google ADK

Use Sequenzy MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Sequenzy MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Sequenzy MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Sequenzy MCP with LlamaIndex

CrewAI logo

CrewAI

Use Sequenzy MCP with CrewAI

FAQ

Frequently asked questions

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

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

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