How to integrate JoggAI MCP with OpenAI Agents SDK

This guide walks you through connecting JoggAI to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working JoggAI agent that can generate your scripts, animate avatars, create product videos, sync lips to audio, and manage webhooks through natural language commands. This guide will help you understand how to give your OpenAI Agents SDK agent real control over a JoggAI account through Composio's JoggAI MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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JoggAI is an AI video creation platform for avatar, product, lip-sync, template, and translated videos. It helps teams turn scripts, products, and media assets into polished videos through APIs.

36 Tools

Introduction

This guide walks you through connecting JoggAI to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working JoggAI agent that can generate your scripts, animate avatars, create product videos, sync lips to audio, and manage webhooks through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a JoggAI account through Composio's JoggAI MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

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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 JoggAI
  • Configure an AI agent that can use JoggAI as a tool
  • Run a live chat session where you can ask the agent to perform JoggAI 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 JoggAI MCP server, and what's possible with it?

The JoggAI MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your JoggAI account. It provides structured and secure access to your avatars, products, videos, templates, scripts, and supporting media assets, so your agent can create videos, generate avatars, translate content, track production tasks, and manage webhooks on your behalf.

  • Avatar and lip-sync video creation: Have your agent create talking-avatar and lip-sync videos, generate photo or product avatars, and animate selected avatar images with speech and motion.
  • Product video production: Let the agent create or update product details, generate scripts and visual previews, then render selected concepts into finished product videos.
  • Template-based video rendering: Direct your agent to produce videos from JoggAI templates using text, scripts, images, videos, avatars, voices, captions, and music.
  • Video translation and dubbing: Instruct your agent to find supported languages and translate videos with options for dubbing, lip sync, subtitles, audio-only output, and adjusted duration.
  • Media tracking and notifications: Have your agent check video and avatar generation progress, browse available voices, music, templates, and visual styles, review account credits, and manage webhook notifications.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live JoggAI project
  • Some knowledge of Python or Typescript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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
3

Install dependencies

npm install @composio/openai-agents @openai/agents dotenv

Install the Composio SDK and the OpenAI Agents SDK.

4

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

5

Import dependencies

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';
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 JoggAI.
6

Set up the Composio instance

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(),
});
What's happening:
  • dotenv.config() loads your .env file so COMPOSIO_API_KEY and USER_ID are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.
7

Create a Tool Router session

// Create Tool Router session for JoggAI
const session = await composio.create(userId as string, {
  toolkits: ['jogg_ai'],
});
const mcpUrl = session.mcp.url;

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only jogg_ai.
  • The router checks the user's JoggAI connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access JoggAI.
  • This approach keeps things lightweight and lets the agent request JoggAI tools only when needed during the conversation.
8

Configure the agent

// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access JoggAI. Help users perform JoggAI operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access JoggAI and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a hostedMcpTool that connects to the MCP server URL we created earlier.
  • The headers object includes the Composio API key for secure authentication with the MCP server.
  • requireApproval: 'never' means the agent can execute JoggAI operations without asking for permission each time, making interactions smoother.
9

Start chat loop and handle conversation

// 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);
});
What's happening:
  • The program prints a session URL that you visit to authorize JoggAI.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using run().
  • The responses are printed to the console.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with JoggAI and OpenAI Agents SDK:

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: ['jogg_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 JoggAI. Help users perform JoggAI 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 JoggAI MCP with OpenAI Agents SDK to build a functional AI agent that can interact with JoggAI.

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.
TOOLS

Supported Tools

Every JoggAI action and event your agent gets out of the box.

Animate Photo Avatar

Create a reusable animated avatar from a photo-avatar image.

Animate Product Avatar

Add motion and a voice to a selected JoggAI product-avatar image generation.

Create Asset Upload URL

Create a signed URL for uploading an asset to JoggAI.

Create Lip Sync Video

Start an asynchronous lip-sync video from publicly reachable video and audio URLs.

Create Product

Create product information from exactly one source: a product page URL, or manually supplied product details.

Create Product Video

Start a product video using a saved product and nested video, avatar, voice, audio, and script settings.

Create Product Video Previews

Generate product-video previews for one or more visual styles.

Create Talking Avatar Video

Start a talking-avatar video using an avatar and either a text script or hosted audio.

Create Template Video

Start rendering a JoggAI v2 template with typed text, script, image, or video variables and optional avatar, voice, captions, and music settings.

Create Webhook

Create a JoggAI webhook endpoint with a callback URL, delivery status, and event subscriptions.

Delete Webhook

Permanently delete one JoggAI webhook endpoint.

Generate AI Scripts

Start asynchronous AI script generation from a saved product or inline product details.

Generate Photo Avatar Image

Start AI photo-avatar image generation using JoggAI's exact demographic, style, model, and aspect-ratio modes.

Generate Product Avatar Images

Start asynchronous generation of one to four product-avatar images from a public product image and an existing avatar, reference image, or description.

Get Account and Credit Balance

Return the connected JoggAI user and remaining credit balance.

Get AI Script Task

Check an AI script generation task and return generated scripts when completed.

Get Lip Sync Video

Check a lip-sync task and return its output URLs and duration when successful.

Get Photo Avatar

Check photo-avatar motion generation and return the reusable avatar details when complete.

Get Photo Avatar Image

Check photo-avatar image generation and return the generated image URLs and keys when ready.

Get Product Avatar

Check product-avatar motion generation and return the reusable avatar when complete.

Get Product Avatar Image Task

Check a product-avatar image generation batch and return its status summary and generated image candidates.

Get Product Video

Check one product video and return its generated media when available.

Get Talking Avatar Video

Check a talking-avatar video and return its media URLs when completed.

Get Template Video

Check a template-rendered video and return its output details when complete.

Get Video Translation

Check a video translation and return translated media when complete.

List Avatars

List public, instant, photo, or product avatars available for JoggAI video generation.

List Creation Assets

Browse one music, template, visual-style, or voice catalog used to create JoggAI media.

List Product Previews

List generated JoggAI product-video previews and their statuses one page at a time.

List Product Videos

List product videos with status and sort filters, one bounded page at a time.

List Translation Languages

Return currently supported lowercase target-language identifiers for JoggAI video translation.

List Webhook Events

Return event identifiers that can be subscribed to by a JoggAI webhook.

List Webhooks

List webhook endpoints registered on the connected JoggAI account.

Render Product Video Preview

Render one selected product preview into a final video.

Translate Video

Start asynchronous video translation with optional audio-only translation, dubbing, lip sync, subtitles, and dynamic duration.

Update Product

Update an existing JoggAI product's descriptive fields.

Update Webhook

Fully replace an existing JoggAI webhook's callback URL, delivery status, and event subscriptions.

FAQ

Frequently asked questions

With a standalone JoggAI MCP server, the agents and LLMs can only access a fixed set of JoggAI tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from JoggAI and many other apps based on the task at hand, all through a single MCP endpoint.

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 JoggAI tools.

Yes, absolutely. You can configure which JoggAI 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.

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 JoggAI data and credentials are handled as safely as possible.

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