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Jsoncut MCP Server

jsoncut

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.

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Repository deprecated - use public server at mcp.jsoncut.comRemote server available with zero setup

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[!WARNING] ⚠️ OUTDATED REPOSITORY - This repository is no longer maintained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

For 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 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


<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>

FAQ

What is the Jsoncut MCP Server MCP server?
Jsoncut MCP Server is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Jsoncut MCP Server?
This profile displays 59 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.659 reviews
  • Ama Iyer· Dec 24, 2024

    Jsoncut MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Shikha Mishra· Dec 16, 2024

    Jsoncut MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • James Gill· Dec 8, 2024

    Jsoncut MCP Server has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Li Martinez· Dec 4, 2024

    Jsoncut MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Aanya Reddy· Nov 27, 2024

    According to our notes, Jsoncut MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Mei Anderson· Nov 23, 2024

    Jsoncut MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Mei Ndlovu· Nov 15, 2024

    Jsoncut MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Rahul Santra· Nov 7, 2024

    Jsoncut MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Pratham Ware· Oct 26, 2024

    Jsoncut MCP Server has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Aanya Singh· Oct 18, 2024

    Jsoncut MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

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