How to integrate Zoho inventory MCP with Autogen

This guide walks you through connecting Zoho inventory to AutoGen using the Composio tool router. By the end, you'll have a working Zoho inventory agent that can check current stock for a specific item, list all pending sales orders today, create a new purchase order for supplier through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Zoho inventory account through Composio's Zoho inventory MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Zoho inventory logoZoho inventory
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Zoho Inventory is a cloud-based inventory and order management solution for businesses. It streamlines stock tracking, order fulfillment, and multi-channel inventory control.

58 Tools

Introduction

This guide walks you through connecting Zoho inventory to AutoGen using the Composio tool router. By the end, you'll have a working Zoho inventory agent that can check current stock for a specific item, list all pending sales orders today, create a new purchase order for supplier through natural language commands.

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

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

Also integrate Zoho inventory with

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 inventory
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Zoho inventory tools
  • Run a live chat loop where you ask the agent to perform Zoho inventory 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 inventory MCP server, and what's possible with it?

The Zoho inventory 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 Inventory account. It provides structured and secure access to your inventory management system, so your agent can perform actions like tracking stock levels, managing sales and purchase orders, updating product details, and syncing inventory across sales channels on your behalf.

  • Real-time stock tracking and updates: Let your agent monitor inventory levels, adjust quantities, and receive alerts when items are running low or out of stock.
  • Order management automation: Have the agent create, update, or track sales and purchase orders, making it easy to keep tabs on every transaction.
  • Product catalog management: Direct your agent to add new products, update existing details, or manage pricing and SKU information to keep your catalog current and accurate.
  • Multi-channel inventory syncing: Enable your agent to synchronize inventory data across multiple online stores and marketplaces, ensuring consistency and reducing errors.
  • Shipment and fulfillment handling: Empower your agent to generate shipment orders, track deliveries, and manage warehouse operations for streamlined fulfillment.

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 inventory 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 inventory 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 inventory 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 inventory session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["zoho_inventory"]
    )
    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 inventory 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 inventory assistant agent with MCP tools
    agent = AssistantAgent(
        name="zoho_inventory_assistant",
        description="An AI assistant that helps with Zoho inventory 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 inventory 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 inventory 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 inventory 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 inventory 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 inventory session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["zoho_inventory"]
    )
    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 inventory assistant agent with MCP tools
        agent = AssistantAgent(
            name="zoho_inventory_assistant",
            description="An AI assistant that helps with Zoho inventory 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 inventory 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 inventory 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 inventory, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Add Credit Note Comment

Tool to add a comment to a credit note in Zoho Inventory.

Add Invoice Attachment

Tool to upload an attachment to a specific invoice.

Add Invoice Comment

Tool to add a comment to a specific invoice in Zoho Inventory.

Apply Credits To Invoices

Tool to apply credits from a credit note to one or more invoices.

Bulk Delete Sales Orders

Tool to bulk delete sales orders.

Bulk Email Invoices

Sends multiple invoices by email to a contact in a single API call.

Bulk Export Invoices

Tool to bulk export invoices as a single PDF.

Bulk Print Invoices

Generate a consolidated PDF containing multiple invoices for printing or archiving.

Bulk Print Packages

Tool to bulk print package slips as a consolidated PDF.

Cancel Invoice Write Off

Tool to cancel write off for an invoice.

Create Bill

Tool to create a bill in Zoho Inventory.

Create Contact

Tool to create a new contact (customer or vendor) in Zoho Inventory.

Create Contact Person

Tool to create a contact person.

Create Credit Note

Tool to create a new credit note in Zoho Inventory.

Create Customer Payment

Tool to create a customer payment in Zoho Inventory.

Create Invoice

Tool to create a new invoice in Zoho Inventory.

Create Item

Tool to create a new item in Zoho Inventory.

Create Item Group

Tool to create an item group in Zoho Inventory.

Create Package

Tool to create a package for a sales order in Zoho Inventory.

Create Purchase Order

Tool to create a purchase order in Zoho Inventory.

Create Sales Order

Tool to create a sales order in Zoho Inventory.

Deactivate Contact

Tool to mark a contact as inactive in Zoho Inventory.

Deactivate Item

Tool to mark an item as inactive in Zoho Inventory.

Deactivate Item Group

Tool to mark an item group as inactive in Zoho Inventory.

Delete Composite Item

Permanently deletes a composite item from Zoho Inventory.

Delete Contact

Tool to delete a contact.

Delete Contact Person

Tool to delete a contact person.

Delete Invoice

Tool to delete an invoice.

Delete Invoice Attachment

Tool to delete an invoice attachment.

Delete Invoice Comment

Delete a specific comment from an invoice in Zoho Inventory.

Delete Item

Tool to delete an item.

Delete Item Group

Tool to delete an item group.

Delete Item Image

Tool to delete an image associated with an item.

Delete Package

Tool to delete a package.

Delete Sales Order

Tool to delete a sales order.

Disable Payment Reminder

Tool to disable payment reminders for an invoice.

Email Contact

Tool to email a contact in Zoho Inventory.

Email Contact Statement

Tool to email a statement of transactions to a contact.

Email Credit Note

Tool to email a credit note to customers.

Email Invoice

Tool to email a specific invoice to customers.

Enable Invoice Payment Reminder

Tool to enable payment reminders for an invoice.

Get Contact

Tool to retrieve a specific contact by ID from Zoho Inventory.

Get Contact Address

Tool to get contact address.

Get Credit Note

Tool to retrieve a credit note by ID.

Get Credit Note Email Content

Tool to get credit note email content including subject, body, recipients, and available templates.

Get Current User

Tool to get details of the currently authenticated user in Zoho Inventory.

Get Sales Order

Tool to retrieve the details of an existing sales order.

List Bills

Tool to list bills.

List Contacts

Tool to list all contacts (customers and vendors) in Zoho Inventory.

List Credit Notes

Tool to list all credit notes.

List Currencies

Tool to list all currencies configured in Zoho Inventory.

List Invoice Payments

Tool to list all payments received for a specific invoice.

List Invoices

Tool to list all invoices in Zoho Inventory.

List Item Groups

Tool to list all item groups in Zoho Inventory.

List Items

Tool to list all items in Zoho Inventory.

List Organizations

Tool to list all organizations the user has access to in Zoho Inventory.

List Purchase Orders

Tool to list purchase orders.

List Sales Orders

Tool to list sales orders.

FAQ

Frequently asked questions

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

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

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