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How to integrate Zoho desk MCP with Autogen

Connect Autogen to Zoho desk MCP. List high-priority open support tickets, summarize recent customer interactions today, and more using natural language, with authentication handled for you.

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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.

36 Tools

Introduction

This guide walks you through connecting Zoho desk to AutoGen using the Composio tool router. By the end, you'll have a working Zoho desk agent that can create and update tickets, read ticket threads and comments, manage contacts, list agents and departments, and upload attachments through natural language commands.

This guide will help you understand how to give your AutoGen 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

Claude CodeCursorChatGPTClaude CoworkAntigravityOpenAI Agents SDKClaude Agent SDKCodexGrok BuildVS CodeOpenCodeOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIPydantic AI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Zoho desk
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Zoho desk tools
  • Run a live chat loop where you ask the agent to perform Zoho desk operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Zoho desk account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Zoho desk via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Zoho desk connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Zoho desk session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["zoho_desk"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Zoho desk tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Zoho desk assistant agent with MCP tools
    agent = AssistantAgent(
        name="zoho_desk_assistant",
        description="An AI assistant that helps with Zoho desk operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Zoho desk tools from the workbench
8

Run the interactive chat loop

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

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Zoho desk tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Zoho desk and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Zoho desk session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["zoho_desk"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Zoho desk assistant agent with MCP tools
        agent = AssistantAgent(
            name="zoho_desk_assistant",
            description="An AI assistant that helps with Zoho desk operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

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

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Zoho desk through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Zoho desk, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Create Contact

Tool to create a new contact in Zoho Desk with name, email, and other details.

Create Ticket

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

Download Ticket Attachment

Download a file attachment from a Zoho Desk ticket by attachment ID.

Get Account

Retrieve one Zoho Desk customer account by its account ID.

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 Agents

Tool to list all agents in the Zoho Desk organization with optional filtering and pagination.

List Contact Accounts

Lists accounts associated with a Zoho Desk contact.

List Contacts

Tool to list contacts with filters and pagination.

List Contact Tickets

List one offset-limited page of tickets raised by a Zoho Desk contact.

List Departments

List 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 Comments

List comments recorded on a Zoho Desk ticket.

List Ticket Conversations

List Ticket Conversations

List Ticket History

List audit and activity history for a ticket.

List Tickets

List Tickets

List Ticket Threads

List message threads recorded on a Zoho Desk ticket.

List Views

List all ticket views in the Zoho Desk organization with pagination support.

Search

Search Zoho Desk tickets, accounts, contacts, and tasks by keyword or phrase, across all modules or within a selected module.

Update Account

Tool to update an existing Zoho Desk account's information such as name, email, phone, website, or description.

Update Many Tasks

Update one field across multiple Zoho Desk tasks in a single call, for up to 50 task IDs.

Update Ticket

Updates an existing Zoho Desk ticket by modifying provided fields such as status, priority, assignee, or description.

Upload Department Logo

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

Upload Ticket Attachment

Uploads a file attachment to a specific Zoho Desk ticket.

FRAMEWORKS

How to build Zoho desk MCP Agent with another framework

Claude Code logo

Claude Code

Use Zoho desk MCP with Claude Code

Cursor logo

Cursor

Use Zoho desk MCP with Cursor

ChatGPT logo

ChatGPT

Use Zoho desk MCP with ChatGPT

Claude Cowork logo

Claude Cowork

Use Zoho desk MCP with Claude Cowork

Antigravity logo

Antigravity

Use Zoho desk MCP with Antigravity

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

Codex logo

Codex

Use Zoho desk MCP with Codex

Grok Build logo

Grok Build

Use Zoho desk MCP with Grok Build

VS Code logo

VS Code

Use Zoho desk MCP with VS Code

OpenCode logo

OpenCode

Use Zoho desk MCP with OpenCode

OpenClaw logo

OpenClaw

Use Zoho desk MCP with OpenClaw

Hermes logo

Hermes

Use Zoho desk MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Zoho desk MCP with Atomic Agent

Google ADK logo

Google ADK

Use Zoho desk MCP with Google ADK

LangChain logo

LangChain

Use Zoho desk MCP with LangChain

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

Pydantic AI logo

Pydantic AI

Use Zoho desk MCP with Pydantic AI

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. Autogen 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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