ai-mldeveloper-tools

Sketch

mater1996

by mater1996

Sketch processes design files, extracts internal structure, and renders SVGs for automated design analysis and design-to

Processes Sketch design files by extracting internal structure, analyzing design elements, and rendering visual components as SVG images for design-to-code workflows and automated design analysis.

github stars

11

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

90% token consumption reduction16 specialized analysis toolsNo installation required with npx

best for

  • / Design-to-code automation workflows
  • / AI-powered design analysis
  • / Automated design system documentation
  • / Design file inspection and debugging

capabilities

  • / Load and parse Sketch design files
  • / Extract node positions and detailed design information
  • / Search nodes by name patterns
  • / Render design components as SVG images
  • / Analyze page structures and hierarchies
  • / Process Symbol Masters and Instances

what it does

Processes Sketch design files to extract design elements, analyze structure, and convert components to SVG for automated design-to-code workflows.

about

Sketch is a community-built MCP server published by mater1996 that provides AI assistants with tools and capabilities via the Model Context Protocol. Sketch processes design files, extracts internal structure, and renders SVGs for automated design analysis and design-to It is categorized under ai ml, developer tools. This server exposes 17 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install Sketch 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

Sketch is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Sketch MCP Server

English | 中文

A Sketch file processing server based on Model Context Protocol (MCP), designed for AI tools to intelligently analyze Sketch design files and generate code.

✨ Core Features

  • 🎨 Sketch File Analysis: Comprehensive parsing of Sketch files, extracting nodes, styles, hierarchies, and complete information
  • 🚀 Smart Token Optimization: Up to 90% token consumption reduction, significantly lowering AI call costs
  • 🔍 Intelligent Query System: 16 professional tools for efficient discovery and analysis of design elements
  • 🎯 Symbol Component Support: Complete Symbol Master and Instance processing capabilities
  • 🖼️ Visual Rendering: Render design nodes as SVG/PNG images for AI analysis
  • 📊 Detailed Statistical Analysis: Comprehensive statistics for documents and nodes
  • 🔧 CLI Tool Support: Support for direct npx calls without installation

📦 Installation

Global Installation (Recommended)

npm install -g sketch-mcp-server

Using npx (No Installation Required)

npx sketch-mcp-server

Local Project Installation

npm install sketch-mcp-server

🚀 Quick Start

Command Line Launch

# Start MCP server (stdio mode)
sketch-mcp-server

# Or use npx
npx sketch-mcp-server

AI Tool Integration

This server is designed for the following AI development environments:

  • Trae AI: As an MCP server for Sketch file analysis
  • Cursor: Configure as MCP tool for design-to-code workflow
  • Claude Desktop: For Sketch file processing and analysis

Trae AI Configuration Example

Add MCP server configuration in Trae AI:

{
  "mcpServers": {
    "sketch-mcp-server": {
      "command": "npx",
      "args": ["sketch-mcp-server"]
    }
  }
}

🛠️ Tool List

📁 File Loading Tools

Tool NameDescription
loadSketchByPathLoad Sketch file from file system
loadSketchByConfigLoad Sketch data from configuration object

📊 Document Structure Tools

Tool NameDescriptionOptimization Features
getDocumentStructureGet complete document hierarchy🚀 Supports field filtering and summary mode
getPageStructureGet single page structure-
listPagesList all page basic information-

🎯 Node Query Tools

Tool NameDescriptionToken Optimization
getNodesSummarySmart Node Summary🔥 80-90% Token Reduction
listNodesList nodes (with filtering support)-
listNodesByPageList nodes by page-
findNodesByNameSearch nodes by name-

🔍 Detailed Information Tools

Tool NameDescription
getNodeInfoGet detailed information for single node
getMultipleNodeInfoBatch get node information (up to 100)
getNodePositionGet node position information

🔄 Symbol Component Tools

Tool NameDescription
getSymbolMastersGet all Symbol Masters
getSymbolInstancesGet all Symbol Instances
getSymbolMasterBySymbolIDFind Master by Symbol ID
getSymbolInstanceStylesGet instance styles (including override styles)

🎨 Visualization Tools

Tool NameDescription
renderNodeAsBase64Render node as image (SVG/PNG)

💡 Token Optimization Strategy

Data Volume Comparison

Tool/ModeToken ReductionUse Case
getNodesSummary80-90%Initial analysis, understanding overall structure
getDocumentStructure (summary mode)70-85%Quick document structure overview
getDocumentStructure (field filtering)30-50%Structural analysis
Full mode0%Detailed design requirements

Recommended Workflow

  1. 🔍 Quick Analysis: Use getNodesSummary to understand overall design structure
  2. 📋 Structure Analysis: Use field-filtered getDocumentStructure to get hierarchical relationships
  3. 🎯 Detailed Information: Get detailed information for specific nodes as needed
  4. 👁️ Visual Verification: Render key components to confirm effects

📝 Usage Examples

Basic Workflow

// 1. Load Sketch file
{
  "name": "loadSketchByPath",
  "arguments": {
    "path": "/path/to/design.sketch"
  }
}

// 2. Get smart summary (save 80-90% tokens)
{
  "name": "getNodesSummary",
  "arguments": {
    "groupBy": "type",
    "includeStats": true,
    "maxSamples": 5
  }
}

// 3. Get detailed information for specific nodes
{
  "name": "getMultipleNodeInfo",
  "arguments": {
    "nodeIds": ["button-id", "text-id"]
  }
}

// 4. Render node as image
{
  "name": "renderNodeAsBase64",
  "arguments": {
    "nodeId": "button-id",
    "format": "svg"
  }
}

Advanced Optimization Examples

// Use field filtering to reduce data volume
{
  "name": "getDocumentStructure",
  "arguments": {
    "fields": ["id", "name", "type", "children"],
    "maxDepth": 3,
    "summaryMode": false
  }
}

// Smart summary grouped by style
{
  "name": "getNodesSummary",
  "arguments": {
    "groupBy": "style",
    "includeStats": true,
    "maxSamples": 3
  }
}

🎯 Tool Selection Guide

Use CaseRecommended ToolToken EfficiencyDescription
Understanding overall structuregetNodesSummary⭐⭐⭐⭐⭐Most efficient overview method
Analyzing page hierarchygetDocumentStructure (filtered)⭐⭐⭐⭐Structured hierarchical information
Finding specific nodesfindNodesByName⭐⭐⭐Precise search
Getting detailed informationgetMultipleNodeInfo⭐⭐Batch retrieval
Handling Symbol componentsgetSymbolMasters⭐⭐⭐Component-based design
Visual confirmationrenderNodeAsBase64⭐⭐Intuitive effect viewing

🔧 Development Guide

Environment Requirements

  • Node.js >= 16.0.0
  • npm or yarn

Local Development

# Clone project
git clone https://github.com/mater1996/sketch-mcp-server.git
cd sketch-mcp-server

# Install dependencies
npm install

# Build project
npm run build

# Run tests
npm test

# Start development server
npm run start:mcp

Available Scripts

npm run build          # Build TypeScript to JavaScript
npm run test           # Run test suite
npm run test:coverage  # Run tests and generate coverage report
npm run start          # Start HTTP server
npm run start:mcp      # Start MCP stdio server
npm run release        # Release new version
npm run release:dry    # Simulate release process

📚 API Reference

For detailed API documentation, please refer to Tool Usage Guide.

Development Standards

  • Write code in TypeScript
  • Follow existing code style
  • Add tests for new features
  • Update relevant documentation

📄 License

MIT License

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📞 Support

If you encounter any issues or have questions, please:

  1. Check the documentation
  2. Search existing issues
  3. Create a new issue if needed

FAQ

What is the Sketch MCP server?
Sketch 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 Sketch?
This profile displays 68 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.4 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.

List & Promote Your MCP Server

Share your MCP server with the developer community

GET_STARTED →
MCP server reviews

Ratings

4.468 reviews
  • Ama Shah· Dec 16, 2024

    We wired Sketch into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Harper Khan· Dec 16, 2024

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

  • Luis Kim· Dec 12, 2024

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

  • Pratham Ware· Dec 8, 2024

    Strong directory entry: Sketch surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Daniel Nasser· Dec 4, 2024

    Useful MCP listing: Sketch is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Ama Verma· Dec 4, 2024

    Strong directory entry: Sketch surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Yash Thakker· Nov 27, 2024

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

  • Emma Desai· Nov 27, 2024

    Useful MCP listing: Sketch is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Advait Thomas· Nov 23, 2024

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

  • Daniel Farah· Nov 11, 2024

    Sketch reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

showing 1-10 of 68

1 / 7