How to integrate Zoho desk MCP with LangChain

This guide walks you through connecting Zoho desk to LangChain using the Composio tool router. By the end, you'll have a working Zoho desk agent that can list high-priority open support tickets, summarize recent customer interactions today, create new ticket for incoming email through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Zoho desk account through Composio's Zoho desk MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Zoho Desk is a context-aware helpdesk platform that helps support teams track, manage, and resolve customer tickets. It streamlines workflows and gives you actionable insights into every customer interaction.

23 Tools

Introduction

This guide walks you through connecting Zoho desk to LangChain using the Composio tool router. By the end, you'll have a working Zoho desk agent that can list high-priority open support tickets, summarize recent customer interactions today, create new ticket for incoming email through natural language commands.

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

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

Also integrate Zoho desk with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

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

The Zoho desk MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zoho Desk account. It provides structured and secure access to your helpdesk workspace, so your agent can perform actions like tracking support tickets, managing customer conversations, automating ticket workflows, and generating support insights on your behalf.

  • Ticket tracking and management: Let your agent create, update, and monitor support tickets, ensuring customer inquiries are handled efficiently.
  • Automated workflow execution: Empower your agent to automate repetitive support processes, such as assigning tickets or escalating issues based on rules.
  • Customer communication handling: Enable your agent to fetch and organize customer conversations, keeping your team informed and responsive.
  • Insightful analytics and reporting: Have your agent generate detailed reports and metrics on ticket trends, response times, and agent performance for better decision-making.
  • Collaboration with support teams: Allow your agent to coordinate with team members by tagging, commenting, or sharing ticket information securely within Zoho Desk.

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 Zoho desk 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 Zoho desk 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: ['zoho_desk']
    }
);

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

Configure the agent with the MCP URL

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

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

Create Ticket

Tool to create a new Zoho Desk ticket with subject, description, department, and requester details.

Get Agent

Tool to fetch details of a Zoho Desk agent.

Get Agents Count

Tool to get the total count of agents in Zoho Desk.

Get Contact

Tool to fetch details of a Zoho Desk contact.

Get Contacts By IDs

Tool to fetch multiple contacts by their IDs using Zoho Desk's contactsByIds endpoint.

Get Department

Tool to fetch details of a Zoho Desk department by ID.

Get Department Logo

Tool to get/download a department's logo from Zoho Desk.

Get Departments Count

Tool to get the total count of departments in Zoho Desk.

Get Ticket

Get Ticket

Get Ticket Latest Thread

Tool to fetch the most recent thread of a ticket.

Get Ticket Resolution

Get Ticket Resolution

Get Ticket Thread

Tool to fetch a specific thread within a Zoho Desk ticket.

List Contact Accounts

Tool to list accounts associated with a Zoho Desk contact.

List Contacts

Tool to list contacts with filters and pagination.

List Departments

Tool to list all departments in the current Zoho Desk organization.

List Organizations

Tool to list all organizations the current user belongs to.

List Roles

List Roles

List Roles By IDs

List Roles By IDs

List Teams in Department

Tool to list teams in the specified Zoho Desk department.

List Ticket Conversations

List Ticket Conversations

List Tickets

List Tickets

Update Many Tasks

Update multiple tasks in a single call using Zoho Desk API.

Upload Department Logo

Tool to upload/update a department logo in Zoho Desk.

FRAMEWORKS

How to build Zoho desk MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Zoho desk MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Zoho desk MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Zoho desk MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Zoho desk MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Zoho desk MCP with Claude Cowork

Codex logo

Codex

Use Zoho desk MCP with Codex

Cursor logo

Cursor

Use Zoho desk MCP with Cursor

OpenClaw logo

OpenClaw

Use Zoho desk MCP with OpenClaw

Hermes logo

Hermes

Use Zoho desk MCP with Hermes

CLI logo

CLI

Use Zoho desk MCP with CLI

Google ADK logo

Google ADK

Use Zoho desk MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Zoho desk MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Zoho desk MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Zoho desk MCP with LlamaIndex

CrewAI logo

CrewAI

Use Zoho desk MCP with CrewAI

OpenCode logo

OpenCode

Use Zoho desk MCP with OpenCode

VS Code logo

VS Code

Use Zoho desk MCP with VS Code

FAQ

Frequently asked questions

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

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

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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.

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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.

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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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