How to integrate JoggAI MCP with Claude Agent SDK

This guide walks you through connecting JoggAI to the Claude Agent 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 Claude Agent 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 Claude Agent 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 Claude Agent 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 Claude/Anthropic 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 Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.

Key features include:

  • Native MCP Support: Built-in support for Model Context Protocol servers
  • Permission Modes: Control tool execution permissions
  • Streaming Responses: Real-time response streaming for interactive applications
  • Context Manager: Clean async context management for sessions

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 Claude/Anthropic API Key
  • Primary know-how of Claude Agents SDK
  • A JoggAI account
  • Some knowledge of Python
2

Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
  • Go to the Anthropic Console and create an API key. You'll need credits to use the models.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

npm install @anthropic-ai/claude-agent-sdk @composio/core dotenv

Install the Composio SDK and the Claude Agents SDK.

What's happening:

  • @composio/core provides Composio integration for Anthropic
  • @anthropic-ai/claude-agent-sdk is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID identifies the user for session management
  • ANTHROPIC_API_KEY authenticates with Anthropic/Claude
5

Import dependencies

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

dotenv.config();
What's happening:
  • We're importing all necessary libraries including the Claude Agent SDK and Composio
  • The dotenv.config() function loads environment variables from your .env file
  • This setup prepares the foundation for connecting Claude with JoggAI functionality
6

Create a Composio instance and Tool Router session

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });

  // Create Tool Router session for JoggAI
  const session = await composio.create(USER_ID, {
    toolkits: ['jogg_ai'],
  });
  const mcpUrl = session?.mcp.url;
What's happening:
  • The function checks for the required COMPOSIO_API_KEY environment variable
  • We're creating a Composio instance using our API key
  • The create method creates a Tool Router session for JoggAI
  • The returned url is the MCP server URL that your agent will use
7

Configure Claude Agent with MCP

const options: Options = {
  permissionMode: 'bypassPermissions',
  mcpServers: {
    composio: {
      type: 'http',
      url: mcpUrl,
      headers: { 'x-api-key': COMPOSIO_API_KEY }
    }
  },
  systemPrompt: 'You are a helpful assistant with access to JoggAI tools via Composio.',
  maxTurns: 10,
};
What's happening:
  • We're configuring the Claude Agent options with the MCP server URL
  • permissionMode: 'bypassPermissions' allows the agent to execute operations without asking for permission each time
  • The system prompt instructs the agent that it has access to JoggAI
  • maxTurns: 10 limits the conversation length to prevent excessive API usage
8

Create client and start chat loop

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}
What's happening:
  • The readline interface is created to handle user input and output
  • The query function is used to send the user's input to the agent
  • The chat loop continues until the user types 'exit' or 'quit'
9

Run the application

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}
What's happening:
  • The chat function is the entry point for the application
  • The try-catch block is used to handle any errors that occur

Complete Code

Here's the complete code to get you started with JoggAI and Claude Agent SDK:

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });
  const session = await composio.create(USER_ID, {
    toolkits: ['jogg_ai']
  });
  const mcp_url = session?.mcp.url;

  const options: Options = {
    permissionMode: 'bypassPermissions',
    mcpServers: {
      composio: {
        type: 'http',
        url: mcp_url,
        headers: { 'x-api-key': COMPOSIO_API_KEY }
      }
    },
    systemPrompt: 'You are a helpful assistant with access to JoggAI tools via Composio.',
    maxTurns: 10,
  };

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}

Conclusion

You've successfully built a Claude Agent SDK agent that can interact with JoggAI through Composio's Tool Router.

Key features:

  • Native MCP support through Claude's agent framework
  • Streaming responses for real-time interaction
  • Permission bypass for smooth automated workflows
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.

FRAMEWORKS

How to build JoggAI MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use JoggAI MCP with OpenAI Agents SDK

Claude Code logo

Claude Code

Use JoggAI MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use JoggAI MCP with Claude Cowork

Codex logo

Codex

Use JoggAI MCP with Codex

OpenClaw logo

OpenClaw

Use JoggAI MCP with OpenClaw

Hermes logo

Hermes

Use JoggAI MCP with Hermes

CLI logo

CLI

Use JoggAI MCP with CLI

Google ADK logo

Google ADK

Use JoggAI MCP with Google ADK

LangChain logo

LangChain

Use JoggAI MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use JoggAI MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use JoggAI MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use JoggAI MCP with LlamaIndex

CrewAI logo

CrewAI

Use JoggAI MCP with CrewAI

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. Claude Agent 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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