# How to integrate Zoho MCP with Pydantic AI

```json
{
  "title": "How to integrate Zoho MCP with Pydantic AI",
  "toolkit": "Zoho",
  "toolkit_slug": "zoho",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/zoho/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/zoho/framework/pydantic-ai.md",
  "updated_at": "2026-05-06T08:34:44.462Z"
}
```

## Introduction

This guide walks you through connecting Zoho to Pydantic AI using the Composio tool router. By the end, you'll have a working Zoho agent that can convert new leads to contacts in crm, add a note to an existing zoho deal, list all contacts added this week through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Zoho account through Composio's Zoho MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Zoho with

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

## TL;DR

Here's what you'll learn:
- How to set up your Composio API key and User ID
- How to create a Composio Tool Router session for Zoho
- How to attach an MCP Server to a Pydantic AI agent
- How to stream responses and maintain chat history
- How to build a simple REPL-style chat interface to test your Zoho workflows

## What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.
Key features include:
- Type Safety: Built on Pydantic for automatic data validation
- MCP Support: Native support for Model Context Protocol servers
- Streaming: Built-in support for streaming responses
- Async First: Designed for async/await patterns

## What is the Zoho MCP server, and what's possible with it?

The Zoho 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 account. It provides structured and secure access to your Zoho CRM data, so your agent can perform actions like creating leads, updating records, tagging entries, and managing relationships between your contacts and accounts automatically.
- Automated lead conversion: Instantly convert Zoho CRM leads into contacts, accounts, and even deals without manual effort.
- Effortless CRM record creation: Direct your agent to add new records to any Zoho CRM module—like leads, contacts, or deals—in seconds.
- Bulk record retrieval and updates: Let your agent fetch lists of records or update details across multiple modules to keep your CRM up to date.
- Tag and organize CRM data: Have your agent create and apply new tags for streamlined segmentation and easier tracking of customers or activities.
- Manage cross-module relationships: Enable your agent to associate or update related records between contacts, accounts, and other CRM modules for richer data connections.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ZOHO_CONVERT_ZOHO_LEAD` | Convert Zoho CRM Lead | Converts a lead into a contact, account, and optionally a deal in zoho crm. |
| `ZOHO_CREATE_ZOHO_RECORD` | Create Zoho CRM Record | Creates new records in a specified module in zoho crm. |
| `ZOHO_CREATE_ZOHO_TAG` | Create Zoho CRM Tag | Creates new tags in zoho crm. |
| `ZOHO_GET_ZOHO_RECORDS` | Get Zoho CRM Records | Retrieves records from a specified module in zoho crm. |
| `ZOHO_UPDATE_RELATED_RECORDS` | Update Related Records in Zoho CRM | Associates or updates relationships between records across different modules in zoho crm. |
| `ZOHO_UPDATE_ZOHO_RECORD` | Update Zoho CRM Record | Updates existing records in a specified module in zoho crm. |

## Supported Triggers

None listed.

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

The Zoho MCP server is an implementation of the Model Context Protocol that connects your AI agent to Zoho. It provides structured and secure access so your agent can perform Zoho 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

Before starting, make sure you have:
- Python 3.9 or higher
- A Composio account with an active API key
- Basic familiarity with Python and async programming

### 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

Install the required libraries.
What's happening:
- composio connects your agent to external SaaS tools like Zoho
- pydantic-ai lets you create structured AI agents with tool support
- python-dotenv loads your environment variables securely from a .env file
```bash
pip install composio pydantic-ai python-dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your agent to Composio's API
- USER_ID associates your session with your account for secure tool access
- OPENAI_API_KEY to access OpenAI LLMs
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key
```

### 4. Import dependencies

What's happening:
- We load environment variables and import required modules
- Composio manages connections to Zoho
- MCPServerStreamableHTTP connects to the Zoho MCP server endpoint
- Agent from Pydantic AI lets you define and run the AI assistant
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
```

### 5. Create a Tool Router Session

What's happening:
- We're creating a Tool Router session that gives your agent access to Zoho 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
```python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Zoho
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["zoho"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
```

### 6. Initialize the Pydantic AI Agent

What's happening:
- The MCP client connects to the Zoho endpoint
- The agent uses GPT-5 to interpret user commands and perform Zoho operations
- The instructions field defines the agent's role and behavior
```python
# Attach the MCP server to a Pydantic AI Agent
zoho_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[zoho_mcp],
    instructions=(
        "You are a Zoho assistant. Use Zoho tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
```

### 7. Build the chat interface

What's happening:
- The agent reads input from the terminal and streams its response
- Zoho API calls happen automatically under the hood
- The model keeps conversation history to maintain context across turns
```python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Zoho.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
```

### 8. Run the application

What's happening:
- The asyncio loop launches the agent and keeps it running until you exit
```python
if __name__ == "__main__":
    asyncio.run(main())
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Zoho
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["zoho"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    zoho_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[zoho_mcp],
        instructions=(
            "You are a Zoho assistant. Use Zoho tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Zoho.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

## Conclusion

You've built a Pydantic AI agent that can interact with Zoho through Composio's Tool Router. With this setup, your agent can perform real Zoho actions through natural language.
You can extend this further by:
- Adding other toolkits like Gmail, HubSpot, or Salesforce
- Building a web-based chat interface around this agent
- Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Zoho for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

## How to build Zoho MCP Agent with another framework

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

## Related Toolkits

- [Hubspot](https://composio.dev/toolkits/hubspot) - HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place.
- [Pipedrive](https://composio.dev/toolkits/pipedrive) - Pipedrive is a sales management platform offering pipeline visualization, lead tracking, and workflow automation. It helps sales teams keep deals moving forward efficiently and never miss a follow-up.
- [Salesforce](https://composio.dev/toolkits/salesforce) - Salesforce is a leading CRM platform that helps businesses manage sales, service, and marketing. It centralizes customer data, enabling teams to drive growth and build strong relationships.
- [Apollo](https://composio.dev/toolkits/apollo) - Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place.
- [Attio](https://composio.dev/toolkits/attio) - Attio is a customizable CRM and workspace for managing your team's relationships and workflows. It helps teams organize contacts, automate tasks, and collaborate more efficiently.
- [Acculynx](https://composio.dev/toolkits/acculynx) - AccuLynx is a cloud-based roofing business management software for contractors. It streamlines project tracking, lead management, and document sharing.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Affinity](https://composio.dev/toolkits/affinity) - Affinity is a relationship intelligence CRM that helps private capital investors find, manage, and close more deals. It streamlines deal flow and surfaces key connections to help you win opportunities.
- [Agencyzoom](https://composio.dev/toolkits/agencyzoom) - AgencyZoom is a sales and performance platform built for P&C insurance agencies. It helps agents boost sales, retain clients, and analyze producer results in one place.
- [Bettercontact](https://composio.dev/toolkits/bettercontact) - Bettercontact is a smart contact enrichment tool for finding emails and phone numbers. It helps boost lead generation with automated, waterfall search across multiple sources.
- [Blackbaud](https://composio.dev/toolkits/blackbaud) - Blackbaud provides cloud-based software for nonprofits, schools, and healthcare institutions. It streamlines fundraising, donor management, and mission-driven operations.
- [Brilliant directories](https://composio.dev/toolkits/brilliant_directories) - Brilliant Directories is an all-in-one platform for building and managing online membership communities and business directories. It streamlines listings, member management, and engagement tools into a single, easy interface.
- [Capsule crm](https://composio.dev/toolkits/capsule_crm) - Capsule CRM is a user-friendly CRM platform for managing contacts and sales pipelines. It helps businesses organize relationships and streamline their sales process efficiently.
- [Centralstationcrm](https://composio.dev/toolkits/centralstationcrm) - CentralStationCRM is an easy-to-use CRM software focused on collaboration and long-term customer relationships. It helps teams manage contacts, deals, and communications all in one place.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Close](https://composio.dev/toolkits/close) - Close is a CRM platform built for sales teams, combining calling, email automation, and predictive dialers. It streamlines sales workflows and boosts productivity with all-in-one communication tools.
- [Dropcontact](https://composio.dev/toolkits/dropcontact) - Dropcontact is a B2B email finder and data enrichment service for professionals. It delivers verified email addresses and enriches contact info with up-to-date data.
- [Dynamics365](https://composio.dev/toolkits/dynamics365) - Dynamics 365 is Microsoft's platform combining CRM, ERP, and productivity apps. It streamlines sales, marketing, service, and operations in one place.
- [Espocrm](https://composio.dev/toolkits/espocrm) - EspoCRM is an open-source web application for managing customer relationships. It helps businesses organize contacts, track leads, and streamline their sales process.
- [Fireberry](https://composio.dev/toolkits/fireberry) - Fireberry is a CRM platform that streamlines customer and sales management. It helps businesses organize contacts, automate sales, and integrate with other business tools.

## Frequently Asked Questions

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

With a standalone Zoho MCP server, the agents and LLMs can only access a fixed set of Zoho tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Zoho and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Pydantic AI?

Yes, you can. Pydantic AI 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 tools.

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

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

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