Jsoncut MCP Server

Jsoncut MCP Server

Official
jsoncut

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.

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.

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What it does

  • 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

Best for

Developers building automated visual content generationCreating programmatic image and video workflowsAI agents generating multimedia content
Repository deprecated - use public server at mcp.jsoncut.comRemote server available with zero setup

About Jsoncut MCP Server

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

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.

[!WARNING] ⚠️ OUTDATED REPOSITORY - This repository is no longer maintained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/mcp

For more information, see: https://docs.jsoncut.com/docs/mcp/overview


Jsoncut Logo

Jsoncut MCP Server

Model Context Protocol server for the Jsoncut API
Enable AI agents to generate stunning images and videos programmatically

npm version License


🚀 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 SettingsFeaturesMCP 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 schema
  • schema://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 validate
  • apiKey: 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

  1. Create Configuration: Use create_image_config or create_video_config
  2. Validate (optional): Call validate_config if you have actual file paths
  3. 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 types
  • video-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


Built with the Model Context Protocol SDK by Anthropic

Made with ❤️ by the Jsoncut Team

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