# How to integrate Zoho bigin MCP with LangChain

```json
{
  "title": "How to integrate Zoho bigin MCP with LangChain",
  "toolkit": "Zoho bigin",
  "toolkit_slug": "zoho_bigin",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/zoho_bigin/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/zoho_bigin/framework/langchain.md",
  "updated_at": "2026-05-06T08:34:46.611Z"
}
```

## Introduction

This guide walks you through connecting Zoho bigin to LangChain 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 LangChain 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

- [ChatGPT](https://composio.dev/toolkits/zoho_bigin/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/zoho_bigin/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/zoho_bigin/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/zoho_bigin/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/zoho_bigin/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/zoho_bigin/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/zoho_bigin/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/zoho_bigin/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/zoho_bigin/framework/cli)
- [Google ADK](https://composio.dev/toolkits/zoho_bigin/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/zoho_bigin/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/zoho_bigin/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/zoho_bigin/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/zoho_bigin/framework/crew-ai)

## TL;DR

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ZOHO_BIGIN_ADD_RECORDS` | Add Records | Tool to add new records to a module. use when you need to programmatically insert one or more records into bigin after confirming module name and field api names. provide required fields per module (e.g., contacts requires last name). |
| `ZOHO_BIGIN_ADD_TAGS_TO_RECORDS` | Add Tags to Records | Tool to add tags to a specific record in a module. use when you need to categorize or label a record after creation or update. |
| `ZOHO_BIGIN_CREATE_TAGS` | Create Tags | Tool to create tags for a module. use when you need to add new tags to a specific module in zoho bigin. |
| `ZOHO_BIGIN_DELETE_ATTACHMENT` | Delete Attachment | Tool to delete an attachment from a record. use when you need to remove a file after confirming its record id and attachment id. |
| `ZOHO_BIGIN_DELETE_RECORDS` | Delete Records | Tool to delete records from a module. use when removing one or multiple records after confirming their ids. |
| `ZOHO_BIGIN_DOWNLOAD_ATTACHMENT` | Download Attachment | Tool to download an attachment from a record. use when you need the binary content of a specific attachment after confirming the record and attachment ids. |
| `ZOHO_BIGIN_GET_ATTACHMENTS` | Get Attachments | Tool to retrieve attachments for a record. use when you need a paginated list of attachments for a given module record. |
| `ZOHO_BIGIN_GET_DELETED_RECORDS` | Get Deleted Records | Tool to get a list of deleted records in a module. use when auditing or restoring recently deleted data (recycle within 60 days, permanent within 120 days). |
| `ZOHO_BIGIN_GET_MODULES` | Get Modules | Tool to retrieve a list of all modules. use when you need to discover which modules are available in bigin. |
| `ZOHO_BIGIN_GET_RECORDS` | Get Records | Tool to retrieve records from a bigin module. use when listing or querying module data with specific fields, sorting, filtering, and pagination. |
| `ZOHO_BIGIN_UPDATE_RECORDS` | Update Records | Tool to update existing records in a module. use when you need to modify one or multiple records after confirming their ids and field api names. supports up to 100 records per call; specify an optional trigger to control workflow execution. |
| `ZOHO_BIGIN_UPLOAD_ATTACHMENT` | Upload Attachment | Tool to upload an attachment to a record. use when you need to attach a file or specify a public url for upload to a bigin record. ensure module api name and record id are correct before calling. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Zoho bigin MCP server is an implementation of the Model Context Protocol that connects your AI agent to Zoho bigin. It provides structured and secure access so your agent can perform Zoho bigin operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

No description provided.

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
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();
```

### 5. Initialize Composio client

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 bigin tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
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()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Zoho bigin 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 bigin tools as needed
```python
# Create Tool Router session for Zoho bigin
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['zoho_bigin']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['zoho_bigin']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "zoho_bigin-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "zoho_bigin-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 });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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")

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

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

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Zoho bigin 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);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['zoho_bigin']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "zoho_bigin-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    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")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

```typescript
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_bigin']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "zoho_bigin-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 bigin 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 bigin 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.

## How to build Zoho bigin MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/zoho_bigin/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/zoho_bigin/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/zoho_bigin/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/zoho_bigin/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/zoho_bigin/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/zoho_bigin/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/zoho_bigin/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/zoho_bigin/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/zoho_bigin/framework/cli)
- [Google ADK](https://composio.dev/toolkits/zoho_bigin/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/zoho_bigin/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/zoho_bigin/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/zoho_bigin/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/zoho_bigin/framework/crew-ai)

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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Zoho bigin MCP?

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.

### Can I use Tool Router MCP with LangChain?

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 bigin tools.

### Can I manage the permissions and scopes for Zoho bigin while using Tool Router?

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.

### How safe is my data with Composio Tool Router?

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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