# How to integrate Zixflow MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Zixflow MCP with OpenAI Agents SDK",
  "toolkit": "Zixflow",
  "toolkit_slug": "zixflow",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/zixflow/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/zixflow/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-03-29T06:56:25.114Z"
}
```

## Introduction

This guide walks you through connecting Zixflow to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Zixflow agent that can send a bulk sms campaign to all new leads, add a follow-up reminder for every hot lead, list conversations from whatsapp with unread responses through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Zixflow account through Composio's Zixflow MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Zixflow with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Zixflow
- Configure an AI agent that can use Zixflow as a tool
- Run a live chat session where you can ask the agent to perform Zixflow operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

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

The Zixflow MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zixflow account. It provides structured and secure access so your agent can perform Zixflow operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ZIXFLOW_CREATE_ATTRIBUTE` | Create Attribute | Tool to create a custom attribute for a Zixflow collection or list. Use when you need to add new fields to track specific data types (text, number, email, etc.). Attributes define the structure of your data. Common use cases: adding custom fields for contacts, creating status trackers, adding reference fields between collections. |
| `ZIXFLOW_GET_CAMPAIGN_REPORT_WHATSAPP` | Get WhatsApp Campaign Report | Tool to retrieve WhatsApp campaign message report. Use when you need to check the delivery status and details of a WhatsApp message sent via campaign. |
| `ZIXFLOW_GET_EMAIL_REPORT` | Get Email Report | Tool to retrieve email message delivery report from Zixflow. Use when you need to check the delivery status of a sent campaign email. The report includes delivery status (SENT, OPENED, CLICKED, BOUNCE, COMPLAINT, UNSUBSCRIBED), recipient information, and timestamps. Requires the message ID obtained when sending the campaign. |
| `ZIXFLOW_GET_SMS_REPORT` | Get SMS Report | Tool to retrieve SMS message delivery report from Zixflow. Use when you need to check the delivery status, destination, and other details of a sent SMS campaign message. |
| `ZIXFLOW_GET_WHATSAPP_TEMPLATE_VARIABLES` | Get WhatsApp Template Variables | Tool to retrieve template variable details for a WhatsApp template. Use when you need to understand what variables a specific WhatsApp template expects before sending a message. |
| `ZIXFLOW_LIST_ATTRIBUTE_OPTIONS` | List Attribute Options | Tool to retrieve the list of options for select/multiselect attributes. Use when you need to get available options for a specific attribute in a collection or list. |
| `ZIXFLOW_LIST_ATTRIBUTE_STATUS_OPTIONS` | List Attribute Status Options | Tool to retrieve the list of options for status attributes in Zixflow. Use when you need to fetch available status configurations for a specific attribute within a collection or list. |

## Supported Triggers

None listed.

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

The Zixflow MCP server is an implementation of the Model Context Protocol that connects your AI agent to Zixflow. It provides structured and secure access so your agent can perform Zixflow 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:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Zixflow project
- Some knowledge of Python or Typescript

### 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).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Zixflow.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only zixflow.
- The router checks the user's Zixflow connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Zixflow.
- This approach keeps things lightweight and lets the agent request Zixflow tools only when needed during the conversation.
```python
# Create a Zixflow Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["zixflow"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Zixflow
const session = await composio.create(userId as string, {
  toolkits: ['zixflow'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Zixflow. "
        "Help users perform Zixflow operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Zixflow. Help users perform Zixflow operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["zixflow"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Zixflow. "
        "Help users perform Zixflow operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['zixflow'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Zixflow. Help users perform Zixflow operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\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

This was a starter code for integrating Zixflow MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Zixflow.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Zixflow MCP Agent with another framework

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

## Related Toolkits

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- [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.
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- [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing.
- [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.
- [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages.
- [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections.
- [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.
- [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach.
- [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease.

## Frequently Asked Questions

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

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

### Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Zixflow tools.

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

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

---
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