# How to integrate Wachete MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Wachete MCP with OpenAI Agents SDK",
  "toolkit": "Wachete",
  "toolkit_slug": "wachete",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/wachete/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/wachete/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:29:55.603Z"
}
```

## Introduction

This guide walks you through connecting Wachete to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Wachete agent that can monitor a webpage for price changes, list all your active web watchers, delete a watcher monitoring an old url through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Wachete account through Composio's Wachete MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Wachete with

- [Claude Agent SDK](https://composio.dev/toolkits/wachete/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/wachete/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/wachete/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/wachete/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/wachete/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/wachete/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/wachete/framework/cli)
- [Google ADK](https://composio.dev/toolkits/wachete/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/wachete/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/wachete/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/wachete/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/wachete/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/wachete/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 Wachete
- Configure an AI agent that can use Wachete as a tool
- Run a live chat session where you can ask the agent to perform Wachete 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 Wachete MCP server, and what's possible with it?

The Wachete MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, and more directly to your Wachete account. It provides structured and secure access to your web monitoring setup, so your agent can create watchers, monitor webpages for changes, manage your folders, and keep you notified about updates—all automatically.
- Automated webpage monitoring: Let your agent create new watchers to track changes on any web page or specific elements, so you never miss an update.
- Watcher management and cleanup: Effortlessly remove obsolete monitors by deleting watchers when you no longer need to track certain content.
- Folder structure navigation: Retrieve and explore the content of your Wachete folders, listing all subfolders and active watchers for better organization.
- Real-time change notifications: Instantly pull notifications about detected changes across all your monitored pages, keeping you up to date at a glance.
- Comprehensive watcher overview: Ask your agent to list all configured watchers, making it easy to review, audit, or adjust your monitoring strategy as your needs evolve.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `WACHETE_CREATE_UPDATE_FOLDER` | Create or update folder | Create a new folder or update an existing folder in Wachete. Folders help organize watchers into hierarchical structures. Omit the id parameter to create a new folder, or provide an id to update an existing one. |
| `WACHETE_CREATE_WATCHER` | Create Watcher | Create or update a Wachete watcher to monitor web page changes. Watchers check pages at specified intervals and send alerts when changes are detected. Use SinglePage mode for monitoring a single page, or Portal mode to crawl and monitor multiple linked pages. |
| `WACHETE_DELETE_FOLDER` | Delete folder | Permanently deletes a folder along with all nested subfolders and watchers (monitoring tasks). This is a destructive operation that cannot be undone. Use when you need to remove an entire folder structure. All subfolders and monitoring tasks within the folder will be permanently deleted. Obtain the folder ID from the Get Folder Content action before calling. Example: "Delete the folder with ID 576b3f7e-e126-4e92-9b95-f72a8d187a18" |
| `WACHETE_DELETE_WATCHER` | Delete watcher | Deletes a website monitoring watcher (task) by its unique ID. This operation is idempotent - deleting a non-existent or already-deleted watcher will succeed without error. Use when you need to permanently remove a monitoring task. Obtain the watcher ID from List Watchers or Create Watcher actions before calling. Example: "Delete the watcher with ID 974b65b5-6ccb-4996-812c-5a678c2455e8" |
| `WACHETE_GET_CRAWLER_PAGES` | Get crawler pages | Retrieves all pages monitored by a crawler watcher (portal monitor). Use this to get detailed information about each page being tracked including URLs, last check timestamps, content changes, and error states. Only works with portal-type watchers that monitor multiple pages. |
| `WACHETE_GET_DATA_HISTORY` | Get Data History | Retrieve history for a wachet (monitor). Returns timestamped snapshots of monitored content showing when changes occurred. Supports time range filtering and optional diff with previous value. Use continuationToken for pagination when retrieving large histories. |
| `WACHETE_GET_FOLDER_CONTENT` | Get folder content | Retrieves the contents of a Wachete folder, including subfolders and watcher tasks. Use this tool to: - List all subfolders and tasks in the root folder (omit parentId) - List contents of a specific folder (provide parentId) - Navigate the folder hierarchy using the path breadcrumb - Check task statuses and last check data Returns subfolders, tasks with their monitoring details, folder path, and pagination token. |
| `WACHETE_GET_WATCHER` | Get watcher by ID | Retrieve complete watcher (monitor) definition by ID. Use this to get detailed configuration and current status of a specific monitoring task including URL, XPath selector, alerts, notification endpoints, and latest check results. |
| `WACHETE_LIST_NOTIFICATIONS` | List notifications | Retrieves notifications from Wachete watchers. Returns notifications for all watchers or filtered by specific watcher ID and/or time range. Useful for checking recent changes detected by your web page monitors. |
| `WACHETE_LIST_WATCHERS` | List watchers | List all monitoring watchers (tasks) configured in your Wachete account. Optionally filter by search query. Returns up to 500 watchers with details including name, URL, monitoring settings, and notification configuration. |
| `WACHETE_MOVE_ITEMS_TO_FOLDER` | Move Items to Folder | Move tasks (watchers) and folders to a specified destination folder. Use this to organize your monitoring structure by relocating items within the folder hierarchy. Provide at least one of folderIds or taskIds to move items. Set folderId to null to move items to root level. |

## Supported Triggers

None listed.

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

The Wachete MCP server is an implementation of the Model Context Protocol that connects your AI agent to Wachete. It provides structured and secure access so your agent can perform Wachete 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 Wachete 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 Wachete.
```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 wachete.
- The router checks the user's Wachete connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Wachete.
- This approach keeps things lightweight and lets the agent request Wachete tools only when needed during the conversation.
```python
# Create a Wachete Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["wachete"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Wachete
const session = await composio.create(userId as string, {
  toolkits: ['wachete'],
});
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 Wachete. "
        "Help users perform Wachete 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 Wachete. Help users perform Wachete 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=["wachete"]
)
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 Wachete. "
        "Help users perform Wachete 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: ['wachete'],
  });
  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 Wachete. Help users perform Wachete 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 Wachete MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Wachete.
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 Wachete MCP Agent with another framework

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

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- [Formsite](https://composio.dev/toolkits/formsite) - Formsite lets you build online forms and surveys with drag-and-drop simplicity. Capture, manage, and integrate form responses securely for streamlined workflows.
- [Graphhopper](https://composio.dev/toolkits/graphhopper) - GraphHopper is an enterprise-grade Directions API for routing, optimization, and geocoding across multiple vehicle types. It enables fast, reliable route planning and logistics automation for businesses.
- [Hyperbrowser](https://composio.dev/toolkits/hyperbrowser) - Hyperbrowser is a next-generation platform for scalable browser automation. It empowers AI agents to interact with web apps, automate workflows, and handle browser sessions at scale.
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- [Maintainx](https://composio.dev/toolkits/maintainx) - Maintainx is a cloud-based CMMS for centralizing maintenance data, communication, and workflows. It helps organizations streamline maintenance operations and improve team coordination.
- [Make](https://composio.dev/toolkits/make) - Make is an automation platform that connects your favorite apps and services. Build powerful, custom workflows without writing code.
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## Frequently Asked Questions

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

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

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

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

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