# How to integrate Desktime MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Desktime MCP with OpenAI Agents SDK",
  "toolkit": "Desktime",
  "toolkit_slug": "desktime",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/desktime/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/desktime/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:08:32.821Z"
}
```

## Introduction

This guide walks you through connecting Desktime to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Desktime agent that can list all active projects with tasks, get today's time tracked for each employee, start timing work on 'client website redesign' through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Desktime account through Composio's Desktime MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Desktime with

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

The Desktime MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Desktime account. It provides structured and secure access to your time tracking, project management, and productivity data, so your agent can perform actions like tracking work hours, managing projects, analyzing employee productivity, and reporting on team activities on your behalf.
- Automated project and task management: Create new projects, assign optional starter tasks, and retrieve a comprehensive list of active company projects for streamlined organization.
- Employee and company insights: Instantly fetch detailed company account info, list all employees with their roles and statuses, and access individual employee data for better workforce visibility.
- Time tracking control: Start or stop tracking work on specific projects and tasks, enabling hands-free, accurate logging of work sessions and project contributions.
- Productivity and app usage analysis: Retrieve employee project assignments and application usage data to monitor work habits and identify productivity trends across your team.
- API health and connectivity checks: Use built-in API ping tools to verify Desktime API availability and ensure uninterrupted agent operations.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DESKTIME_CREATE_PROJECT_WITH_TASK` | Create Project with Optional Task | Tool to create a new project with an optional initial task. Use when you need to set up a new DeskTime project programmatically. |
| `DESKTIME_GET_ACCOUNT_DETAILS` | Get Account Details | Retrieves company account configuration including work schedule and timezone settings. This action fetches company-level information such as company name, work hours (start/end times), work duration, working days configuration, time tracking hours, and timezone. No parameters are required. This is useful for understanding the company's work schedule configuration and timezone settings. |
| `DESKTIME_GET_ALL_COMPANY_EMPLOYEES` | Get All Company Employees | Tool to list all employees in the company, including their roles and statuses. Use after confirming valid credentials to fetch the organization’s roster. |
| `DESKTIME_GET_EMPLOYEE` | Get Employee | Tool to retrieve information about a single employee including user info, work settings, and tracking data for a specific date. Use when you need detailed information for one employee. Returns data for the currently logged-in user if no employee ID is specified. |
| `DESKTIME_GET_EMPLOYEE_APPS` | Get Employee Apps | Retrieves employee tracking data including tracked apps for a specific date. Returns data for the currently logged-in user if no employee ID is specified. Use this action to view detailed application usage and productivity data for an employee. |
| `DESKTIME_GET_EMPLOYEE_PROJECTS` | Get Employee Projects | Retrieves comprehensive employee project tracking data including project assignments, time tracking metrics, work hours, and productivity statistics for a specific employee and date. Returns detailed information about: - Employee profile (ID, name, email, group) - Time tracking metrics (online time, productive time, efficiency) - Work schedule (work start/end times, timezone) - Active project details (current project and task being worked on) - Projects list (all projects tracked on the specified date with durations) - Employee status indicators (online, arrived, left, late) Use this action when you need to: - View an employee's project assignments and tracking data - Check time spent on specific projects by an employee - Monitor employee productivity and work hours - Retrieve historical project tracking data for a specific date Both parameters are optional - defaults to current API-key user and today's date. |
| `DESKTIME_GET_EMPLOYEE_PROJECTS_AND_APPS` | Get Employee Basic Data | Retrieve an employee's basic information and daily tracking statistics from DeskTime. Returns employee profile data, work hours, productivity metrics, attendance status, and currently active project. Use this when you need employee time tracking data for a specific date (defaults to today). Note: For detailed project/app usage breakdowns, use the dedicated Get Employee Projects action. |
| `DESKTIME_GET_PROJECTS_LIST` | Get Projects List | Tool to retrieve all active projects for the company, including related tasks. Use when you need projects overview after authentication. |
| `DESKTIME_PING_REQUEST` | Ping DeskTime API | Tool to check the API's availability and confirm the service is operational. Use when you need to verify that the DeskTime API is reachable and responsive. |
| `DESKTIME_START_PROJECT_TASK` | Start Project Task | Starts time tracking for a specified project and optional task in DeskTime. This action begins recording time against the specified project. If a task name is provided, time is also tracked at the task level within that project. Both projects and tasks are created automatically if they don't already exist in the DeskTime account. Use this action when a user wants to: - Begin working on a project and track time - Start a specific task within a project - Switch time tracking to a different project or task Note: Only one project/task can be tracked at a time per user. Starting a new project automatically stops tracking on any previously active project. |
| `DESKTIME_STOP_PROJECT_TASK` | Stop Project Task | Tool to stop tracking time for a specified project and optional task. Use when you have finished work and need to record end time. |

## Supported Triggers

None listed.

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

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

mcp_url = session.mcp.url
```

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

- [Claude Agent SDK](https://composio.dev/toolkits/desktime/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/desktime/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/desktime/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/desktime/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/desktime/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/desktime/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/desktime/framework/cli)
- [Google ADK](https://composio.dev/toolkits/desktime/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/desktime/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/desktime/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/desktime/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/desktime/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/desktime/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.
- [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.
- [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.
- [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.
- [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.
- [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives.
- [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions.
- [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date.
- [Breeze](https://composio.dev/toolkits/breeze) - Breeze is a project management platform designed to help teams plan, track, and collaborate on projects. It streamlines workflows and keeps everyone on the same page.
- [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes.
- [Canny](https://composio.dev/toolkits/canny) - Canny is a platform for managing customer feedback and feature requests. It helps teams prioritize product decisions based on real user insights.
- [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement.

## Frequently Asked Questions

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

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

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

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

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