# How to integrate Delighted MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Delighted MCP with OpenAI Agents SDK",
  "toolkit": "Delighted",
  "toolkit_slug": "delighted",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/delighted/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/delighted/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-03-29T06:30:02.001Z"
}
```

## Introduction

This guide walks you through connecting Delighted to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Delighted agent that can send an nps survey to a customer, show all recent delighted feedback comments, get nps score for last quarter through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Delighted account through Composio's Delighted MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Delighted with

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

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DELIGHTED_ADD_PERSON_TO_AUTOPILOT_EMAIL` | Add Person to Autopilot Email | Tool to add a person to Autopilot or update their properties for email-based surveys. Use when you need to enroll a person in scheduled email surveys or update their custom properties. |
| `DELIGHTED_ADD_PERSON_TO_AUTOPILOT_SMS` | Add Person to Autopilot SMS | Tool to add a person to Autopilot or update their properties for SMS-based surveys. Use when you need to schedule automated survey delivery via SMS. |
| `DELIGHTED_CREATE_PERSON` | Create or Update Person | Tool to create or update a person and schedule a survey email. Use when you need to add a new person to Delighted, update existing person details, or schedule a survey with custom properties for segmentation. |
| `DELIGHTED_DELETE_PENDING_SURVEY_REQUESTS` | Delete Pending Survey Requests | Tool to remove all pending (scheduled but not yet sent) survey requests for a person. Use when you need to cancel all future surveys for a specific email address. |
| `DELIGHTED_DELETE_PERSON` | Delete Person | Tool to remove a person and all associated data from Delighted. Use when you need to permanently delete a person's information. Deletion includes surveys, responses, properties, Autopilot membership, survey history, and unsubscribe/bounce status. |
| `DELIGHTED_GET_AUTOPILOT_EMAIL_CONFIGURATION` | Get Autopilot Email Configuration | Tool to retrieve the current Autopilot configuration for email distribution. Returns configuration details including whether Autopilot is active, survey frequency, and timestamps. |
| `DELIGHTED_GET_AUTOPILOT_SMS_CONFIGURATION` | Get Autopilot SMS Configuration | Tool to retrieve the current Autopilot configuration for SMS distribution. Use when you need to check whether Autopilot is enabled, review survey frequency settings, or examine configuration timestamps for SMS surveys. |
| `DELIGHTED_LIST_AUTOPILOT_SMS_MEMBERSHIPS` | List Autopilot SMS Memberships | Tool to retrieve all Autopilot memberships for SMS distribution platform. Use when you need to list people enrolled in Autopilot SMS or filter by specific person details. |
| `DELIGHTED_LIST_BOUNCED_PEOPLE` | List Bounced People | Tool to retrieve all bounced people for your account, ordered by bounce time (oldest first). Use when you need to identify email addresses that have bounced. Supports pagination via per_page and page parameters, and optional Unix timestamp filters (since, until) to restrict results to specific time ranges. |
| `DELIGHTED_LIST_PEOPLE` | List People | Tool to retrieve all people for your account in creation order. Use when you need to list contacts, filter by email or phone number, or paginate through your people database. Supports cursor-based pagination via Link header and optional time-based filtering. Note: email and phone_number filters are mutually exclusive. |
| `DELIGHTED_LIST_SURVEY_RESPONSES` | List Survey Responses | Tool to retrieve all survey responses for your account with pagination support and optional filtering. Use when you need to access survey feedback data, filter by date range, trend, person, or sort by creation/update time. Supports expanding person details and notes. |
| `DELIGHTED_LIST_UNSUBSCRIBED_PEOPLE` | List Unsubscribed People | Tool to retrieve all unsubscribed people for your account, ordered by unsubscribe time (oldest first). Use when you need to identify people who have unsubscribed. Supports pagination via per_page and page parameters, and optional Unix timestamp filters (since, until) to restrict results to specific time ranges. |
| `DELIGHTED_UNSUBSCRIBE_PERSON` | Unsubscribe Person | Tool to add a person to your unsubscribe list, preventing them from receiving any future surveys via email. Use when you need to permanently unsubscribe someone from all email surveys. This is functionally equivalent to the person clicking Unsubscribe within a survey. |

## Supported Triggers

None listed.

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

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

mcp_url = session.mcp.url
```

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

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

## Related Toolkits

- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
- [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.
- [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.
- [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.
- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.
- [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds.
- [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights.
- [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.
- [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.
- [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly.

## Frequently Asked Questions

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

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

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)