How to integrate Zoho bigin MCP with Autogen

This guide walks you through connecting Zoho bigin to AutoGen using the Composio tool router. By the end, you'll have a working Zoho bigin agent that can add new contact to sales pipeline, list all open deals this week, tag recent leads as 'hot prospects' through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Zoho bigin account through Composio's Zoho bigin MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Zoho bigin logoZoho bigin
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Zoho Bigin is a simple CRM designed for small businesses to manage pipelines and customer relationships. It helps you organize deals, track progress, and streamline sales processes in one place.

54 Tools

Introduction

This guide walks you through connecting Zoho bigin to AutoGen using the Composio tool router. By the end, you'll have a working Zoho bigin agent that can add new contact to sales pipeline, list all open deals this week, tag recent leads as 'hot prospects' through natural language commands.

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

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

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

The Zoho bigin 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 bigin account. It provides structured and secure access to your CRM pipeline data, so your agent can manage contacts, track deals, organize records, handle attachments, and streamline your small business workflows—all on your behalf.

  • Automated record management: Add, update, or delete records in any Zoho bigin module to keep your CRM data accurate and up to date.
  • Tagging and categorization: Create new tags or apply them to records, making it easy to segment contacts, deals, or companies for better organization.
  • Attachment handling: Retrieve, download, or delete attachments associated with your records, letting your agent manage files and documents with ease.
  • Module and data discovery: List available modules and fetch records with sorting, filtering, and pagination—perfect for quickly surfacing the data you need.
  • Deleted records auditing: Access and review recently deleted records for auditing or restoration, helping you maintain data integrity and recover lost information.

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

Supported Tools

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

Add Records

Tool to add new records to a module.

Add Tags to Records

Tool to add tags to a specific record in a module.

Create Bulk Read Job

Tool to create a bulk read job for exporting large amounts of data asynchronously.

Create Notes

Tool to create notes and associate them with records in Zoho Bigin.

Create Record Notes

Tool to create new notes for a specific record.

Create Tags

Tool to create tags for a module.

Delete Attachment

Tool to delete an attachment from a record.

Delete Note

Tool to delete a note from a specific record.

Delete Notes

Tool to delete multiple notes from Zoho Bigin.

Delete Record

Tool to delete a specific record from a module.

Delete Record Photo

Tool to delete a profile photo from a record.

Delete Records

Tool to delete records from a module.

Delink Related Records

Tool to delete the association between a module record and related list records.

Disable Notifications

Tool to disable instant notifications for one or more channels.

Download Attachment

Tool to download an attachment from a record.

Download Bulk Read Result

Tool to download the bulk read job result in ZIP format (containing CSV or ICS export).

Download Record Photo

Tool to download the profile photo associated with a specific record.

Enable Notifications

Tool to enable instant webhook notifications for module events in Bigin.

Get All Notes

Tool to retrieve the list of notes associated with records.

Get Attachments

Tool to retrieve attachments for a record.

Get Bulk Read Job Status

Tool to retrieve the details of a bulk read job performed earlier.

Get Custom View

Tool to get the metadata of a specific custom view configured in a module.

Get Custom Views

Tool to retrieve the list of custom views available for a module.

Get Deleted Records

Tool to get a list of deleted records in a module.

Get Fields

Tool to retrieve field metadata for a Bigin module.

Get Layout

Tool to retrieve details of a specific layout by layout ID.

Get Layouts

Tool to retrieve the list of layouts available for a module.

Get Module Metadata

Tool to retrieve metadata of a specific module by its API name.

Get Modules

Tool to retrieve a list of all modules.

Get Notification Details

Tool to retrieve information about enabled notifications.

Get Organization

Tool to retrieve organization details including name, ID, currency, time zone, and other settings.

Get Profiles

Tool to retrieve the list of available profiles and their properties in an organization.

Get Record

Tool to retrieve details of a specific record in a module using the record ID.

Get Record Notes

Tool to retrieve the list of notes associated with a specific record.

Get Records

Tool to retrieve records from a Bigin module.

Get Records Count

Tool to get the count of records in a Bigin module.

Get Related Lists Metadata

Tool to retrieve the list of related lists metadata for a module.

Get Related Records

Tool to retrieve related records associated with a specific record in a module.

Get Roles

Tool to retrieve the list of available roles and their properties in an organization.

Get Team Pipeline Records

Tool to retrieve pipeline records from Team Pipelines in Zoho Bigin.

Get User

Tool to retrieve details of a specific user using the user identification.

Get Users

Tool to retrieve the list of users in the organization.

Search Records

Tool to search for records in a Bigin module using various criteria.

Update Note

Tool to update an existing note for a specific record in a module.

Update Notification Details

Tool to update notification channel details in Zoho Bigin.

Update Notification Info

Tool to update specific notification information without losing existing data.

Update Records

Tool to update existing records in a module.

Update Related Records

Tool to update related records associated with a specific record in a module.

Update User

Tool to update details of an existing user by user ID.

Update Users

Tool to update details of multiple users in an organization.

Upload Attachment

Tool to upload an attachment to a record.

Upload Organization Photo

Tool to upload or update the brand logo or image for the current organization.

Upload Record Photo

Tool to upload a photo/image to a specific record (e.

Upsert Records

Tool to insert or update records in a module based on unique field values.

FAQ

Frequently asked questions

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

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

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