# How to integrate CrowTerminal MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate CrowTerminal MCP with OpenAI Agents SDK",
  "toolkit": "CrowTerminal",
  "toolkit_slug": "crowterminal",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/crowterminal/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/crowterminal/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-06-18T09:22:23.948Z"
}
```

## Introduction

This guide walks you through connecting CrowTerminal to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working CrowTerminal agent that can debug failing docker build command, automate repeated git cleanup commands, recall yesterday's terminal troubleshooting notes through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a CrowTerminal account through Composio's CrowTerminal MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate CrowTerminal with

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

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CROWTERMINAL_ANALYZE_ENGAGEMENT` | Analyze Agent Engagement | Tool to analyze engagement correlation for every field in your agent's markdown. Use when you need to understand which agent configuration fields drive engagement and get specific recommendations for improvement. Returns similarity to best/worst performing versions and field-by-field analysis. |
| `CROWTERMINAL_COMPARE_MD` | Compare Agent Markdown | Tool to compare your agent's markdown directly with all stored versions. Returns field differences showing which values differ across versions, lists missing fields not present in your current data, and provides version counts. Use when you need to understand how your current agent configuration compares to historical versions. |
| `CROWTERMINAL_CREATE_WEBHOOK` | Create Webhook | Tool to register a new webhook for receiving real-time event notifications from CrowTerminal. Use when you need to set up asynchronous notifications for events like skill updates, data ingestion, or validation blocks. |
| `CROWTERMINAL_DELETE_WEBHOOK` | Delete Webhook | Tool to delete an existing webhook registration. Use when you need to remove a webhook that is no longer needed or should be replaced. |
| `CROWTERMINAL_GET_BYOK_PLATFORM_INTEL` | Get BYOK Platform Intelligence | Tool to get algorithm insights for TikTok, Instagram, and YouTube without client-specific context. Use when you need platform intelligence data for BYOK (Bring Your Own Key) analysis workflows. This endpoint provides raw contextual algorithm data without triggering LLM inference charges. |
| `CROWTERMINAL_GET_CLIENT_MEMORY_CHANGELOG` | Get Client Memory Changelog | Retrieve human-readable change history for a client's memory. Provides a narrative view of how the client's skill data has evolved over time. |
| `CROWTERMINAL_GET_CLIENT_MEMORY_PATTERN` | Get Client Memory Pattern | Tool to track a specific field over time for trend analysis. Use when you need to understand how a particular metric evolved across versions or time periods. |
| `CROWTERMINAL_GET_COMPONENTS_STATUS` | Get Components Status | Tool to get detailed status of each CrowTerminal service component. Returns current health status, latency, and summary statistics for all monitored components (database, cache, APIs, webhooks). Use when checking system health or diagnosing service issues. |
| `CROWTERMINAL_GET_DATA_TYPES` | Get Data Types | Tool to retrieve valid data types for ingestion across platforms. Returns available data types for TikTok, Instagram, and YouTube that can be used for data ingestion operations. |
| `CROWTERMINAL_GET_INCIDENTS` | Get Recent Incidents | Tool to retrieve list of recent incidents from CrowTerminal with duration and affected components. Use when you need to check system status, monitor service health, or investigate recent outages or degradations. |
| `CROWTERMINAL_GET_PLATFORM_INTEL` | Get Platform Intelligence | Tool to retrieve algorithm insights for TikTok, Instagram, and YouTube. Returns platform-wide intelligence about content algorithm behavior and optimization strategies. Use when you need current platform algorithm trends and recommendations. |
| `CROWTERMINAL_GET_SANDBOX_CLIENT` | Get Sandbox Client | Tool to get mock client data for testing in the sandbox environment. Use when you need to test client-related functionality without affecting real data. No authentication required for sandbox endpoints. |
| `CROWTERMINAL_GET_SANDBOX_MEMORY` | Get Sandbox Memory | Tool to retrieve mock memory/skill data for testing purposes. Use when you need to test memory retrieval without affecting real data or requiring authentication. Part of the sandbox testing environment. |
| `CROWTERMINAL_GET_STATUS` | Get Service Status | Retrieve CrowTerminal service status including overall health, component metrics, and uptime data. Use when you need to check the operational status of CrowTerminal services or monitor system health. No authentication required. |
| `CROWTERMINAL_GET_STATUS_HISTORY` | Get Status History | Tool to get 7-day uptime data points ready for visualization and charting. Use when you need historical uptime metrics for monitoring dashboards or status displays. |
| `CROWTERMINAL_GET_UPTIME` | Get Uptime Data | Tool to retrieve historical uptime data for CrowTerminal agents. Use when you need to check system reliability, view uptime percentages for 24h/7d periods, or review recent service incidents. |
| `CROWTERMINAL_INGEST_BULK_DATA` | Bulk Ingest Analytics Data | Tool to bulk ingest up to 50 analytics data points at once to CrowTerminal. Use when you need to efficiently push large amounts of platform analytics data for content creators across social media platforms. Ideal for batch uploads of retention, engagement, views, and other metrics. |
| `CROWTERMINAL_INGEST_DATA` | Ingest Analytics Data | Tool to ingest platform analytics data from TikTok Studio, Instagram Insights, or YouTube Analytics. Use when you need to push retention curves, demographics, traffic sources, or other engagement metrics for analysis. Supports both video-specific and channel-level data ingestion. |
| `CROWTERMINAL_LIST_WEBHOOKS` | List Webhooks | Tool to list all registered webhooks for the authenticated agent. Use when you need to view all webhook subscriptions and their configurations. |
| `CROWTERMINAL_PING_CROWTERMINAL` | Ping CrowTerminal Service | Tool to check CrowTerminal service availability via a simple ping endpoint. Use when you need to verify the service is online and responding. Returns a pong confirmation with a timestamp. |
| `CROWTERMINAL_READ_BULK_MEMORY` | Bulk Read Memory | Tool to read memory for multiple clients at once (up to 50). Use when you need to efficiently retrieve memory data for multiple creators in a single API call. |
| `CROWTERMINAL_REGISTER_AGENT` | Register Agent | Tool to self-register a new agent and obtain an API key. Use when you need to create a new agent identity in CrowTerminal. No authentication required for this endpoint. Rate limited to 5 requests per hour per IP address. |
| `CROWTERMINAL_RUN_SANDBOX_ENGAGEMENT_ANALYSIS` | Sandbox Engagement Analysis | Tool to run mock engagement analysis in the CrowTerminal sandbox environment. Use when you need to test the engagement analysis workflow without affecting real data or when developing and validating agent configurations. |
| `CROWTERMINAL_TEST_WEBHOOK` | Test Webhook | Tool to test a webhook URL by sending a test payload. Use when you need to verify that a webhook endpoint is properly configured and can receive requests. |
| `CROWTERMINAL_UPDATE_WEBHOOK` | Update Webhook | Tool to update an existing webhook configuration in CrowTerminal. Use when you need to modify webhook URL, change event subscriptions, or enable/disable a webhook. |
| `CROWTERMINAL_VALIDATE_PROPOSED_CHANGES` | Validate Proposed Changes | Tool to validate proposed changes against historical data before updating memory. Use when you need to check if proposed changes contradict historical patterns and receive warnings or recommendations. |
| `CROWTERMINAL_VALIDATE_SANDBOX` | Validate Sandbox | Tool to mock validation endpoint for testing in sandbox. Use when you need to test validation logic. Send 'tutorial' in proposedChanges to get a blocked response. |

## Supported Triggers

None listed.

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

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

mcp_url = session.mcp.url
```

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

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

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- [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction.
- [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting.
- [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache.
- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.

## Frequently Asked Questions

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

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

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

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

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