# How to integrate Stack Ai MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Stack Ai MCP with OpenAI Agents SDK",
  "toolkit": "Stack Ai",
  "toolkit_slug": "stack_ai",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/stack_ai/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/stack_ai/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-03-29T06:51:33.473Z"
}
```

## Introduction

This guide walks you through connecting Stack Ai to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Stack Ai agent that can list all running workflows in stack ai, trigger the monthly data sync workflow, get status of recent workflow runs through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Stack Ai account through Composio's Stack Ai MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Stack Ai with

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

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `STACK_AI_CHECK_HEALTH` | Check Health | Tool to check the health status of the Stack AI API. Use to verify API availability and service status. |
| `STACK_AI_GET_ACTION_INPUTS` | Get Action Inputs | Tool to retrieve the input schema for a specific provider action in Stack AI. Use when you need to understand what parameters are required for a provider action. |
| `STACK_AI_GET_ACTION_OUTPUTS` | Get Action Output Schema | Tool to retrieve the output parameters schema for a Stack.ai provider action as JSON schema. Use when you need to understand what data fields an action returns or to validate action outputs. |
| `STACK_AI_GET_CONNECTOR_TYPE_SCHEMA` | Get Connector Type Schema | Tool to retrieve the configuration schema for a specific connector type in Stack AI. Use when you need to understand what parameters are required to configure a connector. |
| `STACK_AI_GET_LICENSE_STATUS` | Get License Status | Tool to retrieve the current Stack AI license status. Use when you need to check license validity, expiration date, or days remaining. |
| `STACK_AI_GET_PROVIDER_DETAILS` | Get Provider Details | Tool to retrieve details of a specific Stack AI tool provider. Use when you need information about available actions, triggers, and configuration for a provider. |
| `STACK_AI_GET_PROVIDER_ACTION_DETAILS` | Get Provider Action Details | Tool to get details of a specific action for a provider. Use when you need information about a provider's action including its parameters, description, and API details. |
| `STACK_AI_GET_PROVIDER_ICON` | Get Provider Icon | Tool to fetch a provider icon image by provider identifier. Use when you need to retrieve the icon for a tool provider. |
| `STACK_AI_GET_PROVIDER_TRIGGER_DETAILS` | Get Provider Trigger Details | Tool to retrieve detailed information about a specific trigger for a provider. Use when you need to understand the configuration, inputs, outputs, or behavior of a specific trigger. |
| `STACK_AI_GET_ROOT` | Get Root | Tool to retrieve information from the Stack AI API root endpoint. Use when you need to verify API connectivity or get basic API information. |
| `STACK_AI_GET_TRIGGER_DETAILS_FROM_PROVIDER` | Get Trigger Details From Provider | Tool to retrieve detailed information about a specific trigger from a provider. Use when you need to get trigger configuration, capabilities, or metadata for a specific provider's trigger. |
| `STACK_AI_GET_TRIGGER_INPUTS` | Get Trigger Inputs | Tool to retrieve the input parameters for a trigger as a JSON schema. Use when discovering what data inputs a specific trigger requires before executing it. |
| `STACK_AI_GET_TRIGGER_OUTPUTS` | Get Trigger Outputs | Tool to retrieve the output schema for a specific trigger in Stack AI. Use when you need to understand what fields a trigger will produce when it fires. This action helps discover the structure of data that will be available from a trigger event, which is useful for configuring workflows and data processing. |
| `STACK_AI_LIST_CONNECTOR_TYPES` | List Connector Types | Tool to list all available connector types from Stack AI. Use when you need to retrieve the available connectors that can be configured. |
| `STACK_AI_LIST_STACK_AI_INTEGRATIONS` | List Stack AI Integrations | Tool to list all available Stack AI integrations. Use when you need to discover available integrations, actions, and triggers in Stack AI. |
| `STACK_AI_LIST_PERMISSION_GROUPS` | List Permission Groups | Tool to list all permission groups with their associated permissions. Use when you need to retrieve available permission groups and their permissions for access control management. |
| `STACK_AI_LIST_PERMISSIONS` | List Permissions | Tool to list all available permissions in Stack AI. Use when you need to view or check available permission types. |
| `STACK_AI_LIST_PROVIDER_TRIGGERS` | List Provider Triggers | Tool to get all available triggers for a specific provider. Use when you need to discover what trigger types are supported by a provider. |
| `STACK_AI_LIST_STACK_AI_ACTIONS` | List Stack AI Actions | Tool to list all available Stack AI tool actions. Use when you need to discover available automation capabilities organized by provider. |
| `STACK_AI_LIST_STACK_AI_PROVIDERS` | List Stack AI Providers | Tool to list all Stack AI tool providers (integrations). Use when you need to discover available integrations and their capabilities. Returns comprehensive information about each provider including available actions, triggers, and metadata. |
| `STACK_AI_LIST_STACK_AI_BUILT_IN_TOOLS` | List Stack AI Built-in Tools | Tool to list all Stack AI built-in tools. Use when you need to discover available Stack AI native tools and their capabilities. |
| `STACK_AI_LIST_STACK_AI_TRIGGERS` | List Stack AI Triggers | Tool to list all available Stack AI tool triggers. Use when you need to discover what triggers are available in the Stack AI platform. |

## Supported Triggers

None listed.

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

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

mcp_url = session.mcp.url
```

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

- [Claude Agent SDK](https://composio.dev/toolkits/stack_ai/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/stack_ai/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/stack_ai/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/stack_ai/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/stack_ai/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/stack_ai/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/stack_ai/framework/cli)
- [Google ADK](https://composio.dev/toolkits/stack_ai/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/stack_ai/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/stack_ai/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/stack_ai/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/stack_ai/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/stack_ai/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.
- [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.
- [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.
- [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.
- [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.
- [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.
- [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.
- [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.
- [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows.
- [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application.
- [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities.
- [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization.
- [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Stack Ai MCP?

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

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

Yes, absolutely. You can configure which Stack Ai 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 Stack Ai 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)