Jsoncut MCP Server▌

by jsoncut
Jsoncut MCP Server: a json image generator and image generation API for programmatic video generation and dynamic image
Enables AI agents to generate JSON configurations for creating images and videos programmatically through the Jsoncut API, with support for layers, positioning, transitions, and validation.
best for
- / Developers building automated visual content generation
- / Creating programmatic image and video workflows
- / AI agents generating multimedia content
capabilities
- / Generate JSON configs for image composition
- / Create JSON configs for video rendering
- / Validate configurations against Jsoncut API
- / Access JSON schemas as MCP resources
- / Configure layers, positioning, and transitions
what it does
Generates JSON configurations for programmatic image and video creation through the Jsoncut API. Includes validation and schema resources for building visual content with layers, transitions, and effects.
about
Jsoncut MCP Server is an official MCP server published by jsoncut that provides AI assistants with tools and capabilities via the Model Context Protocol. Jsoncut MCP Server: a json image generator and image generation API for programmatic video generation and dynamic image It is categorized under developer tools, design.
how to install
You can install Jsoncut MCP Server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Jsoncut MCP Server is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
[!WARNING] ⚠️ OUTDATED REPOSITORY - This repository is no longer maintained
A public MCP server is now available and this package is deprecated.
Please use the official public server instead: https://mcp.jsoncut.com/mcpFor more information, see: https://docs.jsoncut.com/docs/mcp/overview
<p align="center"> <img src="assets/logo.png" alt="Jsoncut Logo" width="200"/> </p> <h1 align="center">Jsoncut MCP Server</h1> <p align="center"> <strong>Model Context Protocol server for the Jsoncut API</strong><br> Enable AI agents to generate stunning images and videos programmatically </p> <p align="center"> <a href="https://www.npmjs.com/package/@jsoncut/mcp-server"><img src="https://img.shields.io/npm/v/@jsoncut/mcp-server.svg" alt="npm version"></a> <a href="https://github.com/jsoncut/jsoncut-mcp-server/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="License"></a> </p>
🚀 Features
- 🎨 Image Generation: Create JSON configurations for image composition with layers, positioning, and effects
- 🎬 Video Generation: Create JSON configurations for video rendering with clips, transitions, and audio
- ✅ Configuration Validation: Validate configs against the Jsoncut API before submission
- 📋 Schema Resources: JSON schemas automatically available as MCP resources
- 🔑 Flexible Authentication: API key via environment variable or .env file
📦 Quick Start
Using npx (Recommended for Local)
export JSONCUT_API_KEY=your_api_key_here
npx -y @jsoncut/mcp-server
Using Remote Server (Recommended)
A public MCP server is available at https://mcp.jsoncut.com. No installation needed - just configure your MCP client with your API key:
{
"jsoncut": {
"url": "https://mcp.jsoncut.com/mcp",
"headers": {
"x-api-key": "your_jsoncut_api_key_here"
}
}
}
Using Docker Locally (Optional)
You can also run your own local server using Docker:
# Pull and run from Docker Hub
docker run -d \
--name jsoncut-mcp \
-p 3210:3000 \
centerbit/jsoncut-mcp-server:latest
# Access at: http://localhost:3210/mcp
Or use Docker Compose:
# Start the service
docker-compose up -d
# Access at: http://localhost:3210/mcp
📖 See DOCKER.md for complete Docker deployment guide
Get Your API Key
Get your Jsoncut API key at jsoncut.com
# Set as environment variable
export JSONCUT_API_KEY=your_api_key_here
# Or create .env file
cp .env.example .env
# Edit .env and add: JSONCUT_API_KEY=your_api_key_here
🎯 MCP Client Configuration
Remote Server (Recommended)
Use the public server at https://mcp.jsoncut.com:
Cursor IDE
Open Cursor Settings → Features → MCP Servers → "+ Add New MCP Server"
{
"jsoncut": {
"url": "https://mcp.jsoncut.com/mcp",
"headers": {
"X-API-Key": "your_jsoncut_api_key_here"
}
}
}
Claude Desktop
Add to your claude_desktop_config.json:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"jsoncut": {
"url": "https://mcp.jsoncut.com/mcp",
"headers": {
"X-API-Key": "your_jsoncut_api_key_here"
}
}
}
}
Local npx Mode
For local development without network access:
Cursor IDE
{
"jsoncut": {
"command": "npx",
"args": ["-y", "@jsoncut/mcp-server"],
"env": {
"JSONCUT_API_KEY": "your_api_key_here"
}
}
}
Claude Desktop
{
"mcpServers": {
"jsoncut": {
"command": "npx",
"args": ["-y", "@jsoncut/mcp-server"],
"env": {
"JSONCUT_API_KEY": "your_api_key_here"
}
}
}
}
Local Docker Server
If you're running your own local Docker server:
Cursor IDE
{
"jsoncut": {
"url": "http://localhost:3210/mcp",
"headers": {
"X-API-Key": "your_jsoncut_api_key_here"
}
}
}
Claude Desktop
{
"mcpServers": {
"jsoncut": {
"url": "http://localhost:3210/mcp",
"headers": {
"X-API-Key": "your_jsoncut_api_key_here"
}
}
}
}
📚 MCP Resources
The server automatically exposes JSON schemas as MCP resources:
schema://image- Complete image generation schemaschema://video- Complete video generation schema
AI agents can read these directly without tool calls for fast access to all configuration options.
🛠️ Available Tools
create_image_config
Create JSON configurations for image generation with a layer-based system.
Layer Types:
- image: Display images with fit modes (cover, contain, fill, inside, outside)
- text: Text with custom fonts, alignment, wrapping, and effects
- rectangle: Rectangular shapes with fill, stroke, and rounded corners
- circle: Circular and elliptical shapes
- gradient: Linear or radial color gradients
Positioning:
- Pixel coordinates:
{ x: 100, y: 50 } - Position strings:
center,top,bottom,top-left,top-right, etc. - Position objects:
{ x: 0.5, y: 0.5, originX: "center", originY: "center" }
Example:
{
"width": 1200,
"height": 630,
"layers": [
{
"type": "gradient",
"x": 0, "y": 0, "width": 1200, "height": 630,
"gradient": {
"type": "linear",
"colors": ["#667eea", "#764ba2"],
"direction": "diagonal"
}
},
{
"type": "text",
"text": "Welcome to Jsoncut",
"position": "center",
"fontSize": 64,
"color": "#ffffff"
}
]
}
create_video_config
Create JSON configurations for video generation with clips, layers, and transitions.
Key Features:
- Clips: Sequential video segments with individual layers
- Layer Types: video, image, title, subtitle, news-title, audio, gradients, and more
- Transitions: 75+ effects (fade, wipe, circle, cube, glitch, zoom, etc.)
- Audio: Background music, multiple tracks, normalization, and ducking
Example:
{
"width": 1920,
"height": 1080,
"fps": 30,
"defaults": {
"duration": 3,
"transition": { "name": "fade", "duration": 1 }
},
"clips": [
{
"layers": [
{ "type": "title", "text": "Welcome", "position": "center" }
]
}
]
}
validate_config
Validate configurations against the Jsoncut API before submission.
Parameters:
type: "image" or "video"config: Configuration object to validateapiKey: Optional API key (uses environment if not provided)
Returns:
- Validation status
- Estimated token cost
- Error details (if any)
- Detected resources with sizes
get_image_schema / get_video_schema
Get complete JSON schemas for image or video generation.
Note: Schemas are also available as MCP resources (schema://image and schema://video) which AI agents can access directly without tool calls.
📖 Workflow
- Create Configuration: Use
create_image_configorcreate_video_config - Validate (optional): Call
validate_configif you have actual file paths - Submit: Use the configuration with the Jsoncut API
The schemas are automatically available as MCP resources, so AI agents have instant access to all configuration options.
📁 File Paths
Use placeholder paths in configurations:
/image/2024-01-15/userXXX/photo.jpg
/video/2024-01-15/userXXX/video.mp4
/audio/2024-01-15/userXXX/music.mp3
/font/2024-01-15/userXXX/CustomFont.ttf
Supported formats:
- Images: png, jpg, jpeg, gif, webp
- Videos: mp4, mov, avi, webm
- Audio: mp3, wav, m4a, aac
- Fonts: ttf, otf, woff, woff2
🧪 Testing
Use the MCP Inspector for interactive testing:
export JSONCUT_API_KEY=your_api_key_here
npm run inspector
🔧 Development
Local Development
# Clone and install
git clone https://github.com/jsoncut/jsoncut-mcp-server.git
cd jsoncut-mcp-server
npm install
# Build
npm run build
# Watch mode
npm run watch
# Run locally
node dist/index.js
Configuration with Local Build
For Cursor/Claude Desktop, use the local build:
{
"jsoncut": {
"command": "node",
"args": ["/absolute/path/to/jsoncut-mcp-server/dist/index.js"],
"env": {
"JSONCUT_API_KEY": "your_api_key_here"
}
}
}
📝 Examples
See the examples/ directory for complete configurations:
image-example.json- Image generation with multiple layer typesvideo-example.json- Video generation with clips and transitions
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
📄 License
MIT License - see LICENSE file for details.
🔗 Links
- API Documentation: docs.jsoncut.com
- Website: jsoncut.com
- GitHub: github.com/jsoncut/jsoncut-mcp-server
- npm: @jsoncut/mcp-server
- Support: support@jsoncut.com
<p align="center"> Built with the <a href="https://github.com/modelcontextprotocol">Model Context Protocol SDK</a> by Anthropic </p> <p align="center"> Made with ❤️ by the Jsoncut Team </p>