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What is The ultimate MCP server for AI video generation.?
The Creatify MCP Server is a comprehensive Model Context Protocol (MCP) server that exposes the full power of Creatify AI's video generation platform to AI assistants, chatbots, and automation tools. Built on top of the robust @tsavo/creatify-api-ts TypeScript client library, this server transforms complex video creation workflows into simple, natural language interactions.
Documentation
๐ฌ Creatify MCP Server
The ultimate MCP server for AI video generation - Bringing Creatify AI's powerful video creation capabilities to every AI assistant in the MCP ecosystem.
๐ Overview
The Creatify MCP Server is a comprehensive Model Context Protocol (MCP) server that exposes the full power of Creatify AI's video generation platform to AI assistants, chatbots, and automation tools. Built on top of the robust @tsavo/creatify-api-ts TypeScript client library, this server transforms complex video creation workflows into simple, natural language interactions.
๐จ Advanced MCP Features:
๐ Prompts - Reusable video creation templates and workflows
๐ Logging - Structured logging with multiple severity levels
๐ Progress Tracking - Real-time updates during video generation
๐ค AI Self-Help - how_to_use tool for AI assistants to understand parameters
๐ Notifications - Real-time status updates and progress notifications
๐ฏ What This Enables
Imagine telling Claude Desktop: "Create a 16:9 avatar video of Anna saying 'Welcome to our product demo' and wait for it to complete" - and having it actually happen. That's the power of this MCP server.
๐๏ธ Built With
Creatify AI API - The world's leading AI video generation platform
git clone https://github.com/TSavo/creatify-mcp.git
cd creatify-mcp
npm install
npm run build
npm link
๐ฌ Live Demo Examples# Create an AI Avatar Video
User: "Create a professional avatar video with Anna saying 'Welcome to our company!' in 16:9 format"
Claude: I'll create a professional avatar video for you using the Creatify MCP Server.
[Uses create_avatar_video tool with:
- text: "Welcome to our company!"
- avatarId: "anna_costume1_cameraA"
- aspectRatio: "16:9"
- voiceId: "en-US-AriaNeural"]
Your professional avatar video has been created! Anna delivers your message with natural lip-sync and professional presentation.
Generate TikTok-Style Short Video
User: "Make a 30-second TikTok video about coffee brewing tips"
Claude: I'll create an engaging short-form video perfect for TikTok!
[Uses create_ai_shorts tool with:
- prompt: "Quick coffee brewing tips with energetic presentation"
- aspectRatio: "9:16"
- duration: 30
- style: "energetic"]
Your TikTok-ready short video is being generated with optimal 9:16 aspect ratio and engaging content!
Convert Website to Video
User: "Turn my product landing page into a marketing video"
Claude: I'll convert your website into a compelling marketing video.
[Uses create_url_to_video tool with:
- url: "https://yourproduct.com"
- aspectRatio: "16:9"
- style: "marketing"]
Your landing page has been transformed into a professional marketing video showcasing your product!
AI-Powered Script Generation
User: "Generate a script for a 60-second product demo video"
Claude: I'll create a compelling script for your product demo.
[Uses generate_ai_script tool with:
- topic: "Product demonstration video"
- scriptType: "commercial"
- duration: 60
- tone: "professional"]
Your script is ready! It includes engaging hooks, clear value propositions, and a strong call-to-action optimized for 60-second format.
Configuration
Set your Creatify API credentials as environment variables:
๐จ Advanced MCP Features## ๐ Using Prompts (Workflow Templates)
AI assistants can now use predefined workflow templates for common video creation scenarios:
Example: Product Demo Workflow
User: "Use the create-product-demo prompt for 'Amazing Widget' with features 'fast, reliable, easy to use' targeting small business owners"
Claude: I'll use the product demo workflow template to create a professional demonstration video.
[Claude automatically follows the complete workflow:
1. Generates an engaging script using generate_ai_script
2. Creates avatar video using create_avatar_video
3. Optimizes for the target audience
4. Includes clear call-to-action]
Available Prompt Templates:
create-product-demo - Professional product demonstrations
create-educational-video - Tutorials and educational content
create-marketing-campaign - Marketing and promotional videos
analyze-video-performance - Video optimization and analysis
๐ Real-time Logging & Progress
The server provides structured logging with multiple severity levels:
[INFO] Creatify MCP Server initialized
[INFO] Creating avatar video {avatarId: "anna_costume1_cameraA", aspectRatio: "16:9"}
[INFO] Waiting for avatar video completion...
[INFO] Avatar video completed {videoId: "video_abc123"}
AI assistants can now understand tool parameters better using the how_to_use tool:
Claude: Let me check how to use the avatar video tool...
[Calls how_to_use tool with toolName: "create_avatar_video"]
[Gets comprehensive documentation with:
- Required parameters with descriptions
- Optional parameters with usage notes
- Real code examples
- Tips and best practices]
Now I understand exactly how to create your avatar video!
With Custom MCP Client
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
const transport = new StdioClientTransport({
command: "creatify-mcp",
env: {
CREATIFY_API_ID: "your-api-id",
CREATIFY_API_KEY: "your-api-key"
}
});
const client = new Client({
name: "my-client",
version: "1.0.0"
});
await client.connect(transport);
// List available tools
const tools = await client.listTools();
console.log("Available tools:", tools.tools.map(t => t.name));
// Create an avatar video
const result = await client.callTool({
name: "create_avatar_video",
arguments: {
text: "Hello, world! This is an AI-generated video.",
avatarId: "anna_costume1_cameraA",
aspectRatio: "16:9",
waitForCompletion: true
}
});
Standalone Server
export CREATIFY_API_ID="your-api-id"
export CREATIFY_API_KEY="your-api-key"
# Run the server
creatify-mcp
Example Prompts for AI Assistants
Once configured with Claude Desktop or another MCP client, you can use natural language prompts like:
"Create a 16:9 avatar video of Anna saying 'Welcome to our product demo' and wait for it to complete"
aspectRatio ("16:9" | "9:16" | "1:1", optional) - Video aspect ratio
waitForCompletion (boolean, optional) - Wait for video completion
generate_text_to_speech
Generate natural-sounding speech from text.
Parameters:
text (string, required) - Text to convert to speech
voiceId (string, required) - Voice ID to use
waitForCompletion (boolean, optional) - Wait for audio completion
get_video_status
Check the status of a video generation task.
Parameters:
videoId (string, required) - Video/task ID to check
videoType (string, required) - Type of task ("lipsync", "url-to-video", etc.)
Resources## creatify://avatars
Returns a JSON list of all available AI avatars with their IDs, names, and metadata.
creatify://voices
Returns a JSON list of all available voices for text-to-speech generation.
creatify://templates
Returns a JSON list of available custom video templates.
creatify://credits
Returns current account credit balance and usage information.
Development
npm install
# Build the project
npm run build
# Run in development mode with auto-reload
npm run dev
# Run tests
npm test
# Lint and format code
npm run check
Contributing
Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
We welcome contributions! Here's how to get started:
๐ ๏ธ Development Setup
git clone https://github.com/TSavo/creatify-mcp.git
cd creatify-mcp
# Install dependencies
npm install
# Set up environment variables
cp .env.example .env\n\n# Edit .env with your API credentials
# Run tests
npm test
# Build the project
npm run build
# Run in development mode
npm run dev
๐งช Testing
npm test
# Run tests in watch mode
npm run test:watch
# Run type checking
npm run type-check
# Run linting
npm run lint
๐ Code Style
We use:
ESLint for code linting
Prettier for code formatting
TypeScript for type safety
Conventional Commits for commit messages
๐ Pull Request Process
Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Make your changes
Add tests for new functionality
Ensure all tests pass (npm test)
Run linting (npm run lint:fix)
Commit your changes (git commit -m 'feat: add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request
๐ License
This project is licensed under the MIT License - see the LICENSE file for details.
๐ Acknowledgments
Creatify AI - For providing the amazing AI video generation platform