# How to integrate Castingwords MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Castingwords MCP with OpenAI Agents SDK",
  "toolkit": "Castingwords",
  "toolkit_slug": "castingwords",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/castingwords/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/castingwords/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:05:47.733Z"
}
```

## Introduction

This guide walks you through connecting Castingwords to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Castingwords agent that can transcribe this podcast episode from its url, check your available transcription balance now, order timestamps upgrade for file 12345 through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Castingwords account through Composio's Castingwords MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Castingwords with

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

The Castingwords MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Castingwords account. It provides structured and secure access to transcription services, so your agent can place new orders, check account balances, manage webhooks, and upgrade or refund audio files on your behalf.
- Seamless transcription ordering: Let your agent initiate new audio or video transcription jobs using just a media URL—no manual uploads needed.
- Account balance and SKU checks: Effortlessly retrieve your prepay balance or list available transcription services and pricing before placing orders.
- Webhook management and testing: Register, verify, and test webhooks to automatically receive transcript completion notifications in your own systems.
- Transcription order management: Upgrade completed jobs (for example, to add timestamps), or cancel and refund audio files before work begins if needed.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CASTINGWORDS_CANCEL_AUDIOFILE` | Cancel and Refund Audio File | Tool to cancel an ordered audio file and issue a refund if applicable. Use when no transcription work has been done on the file (Pre-Processing, Audio Processing, Error states). |
| `CASTINGWORDS_GET_PREPAY_BALANCE` | Get Prepay Balance | Tool to retrieve the current prepay balance for the account. Use when you need to check available funds before placing new transcription orders. |
| `CASTINGWORDS_GET_TRANSCRIPT` | Get Transcript | Tool to retrieve the transcript for a given audiofile in the requested format (txt, doc, rtf, or html). Use after a transcription order has been completed. |
| `CASTINGWORDS_GET_WEBHOOK` | Get registered webhook URL | Tool to retrieve the currently registered webhook URL for account notifications. Use when you need to verify your webhook setup. |
| `CASTINGWORDS_ORDER_TRANSCRIPT` | Order Transcript | Create a transcription order for audio/video files at publicly accessible URLs. Returns order ID and audiofile IDs for tracking. Requires prepaid balance for non-test orders. Use test=true to validate URLs without charges. |
| `CASTINGWORDS_ORDER_UPGRADES` | Order Upgrades | Tool to order an upgrade for a specific audio file. Use after transcription is complete to add items like timestamps or extra editing. Example: 'Order timestamps for file 12345'. |
| `CASTINGWORDS_REGISTER_WEBHOOK` | Register Webhook | Registers a webhook URL to receive CastingWords event notifications. When events occur (e.g., transcript completion, refund issued, difficult audio), CastingWords will POST to your registered URL with event details. Use CASTINGWORDS_GET_WEBHOOK to verify the current webhook, and CASTINGWORDS_TEST_WEBHOOK to test notifications. |
| `CASTINGWORDS_SKU_LIST` | List Available SKUs | Retrieves all available CastingWords transcription service SKUs with pricing. Use this tool to discover available services (transcription, captions, etc.) and their per-minute prices before placing an order. Returns SKU codes needed for order placement. |
| `CASTINGWORDS_TEST_WEBHOOK` | Test Webhook Call | Tool to request a test webhook call for a specific event type. Use after registering a webhook URL to ensure webhook notifications are functioning properly. |

## Supported Triggers

None listed.

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

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

mcp_url = session.mcp.url
```

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

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

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- [Cloudconvert](https://composio.dev/toolkits/cloudconvert) - CloudConvert is a powerful file conversion service supporting over 200 file formats. It streamlines converting, compressing, and managing documents, media, and more, all in one place.
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## Frequently Asked Questions

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

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

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

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

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