ai-ml

SVGMaker

by genwavellc

SVGMaker is an svg generator and creator that converts photos into vector graphic file types, with editing and real-time

Integrates with SVGMaker's API to generate SVGs from text descriptions, edit existing images, and convert bitmap images to vector format with customizable quality settings and real-time progress tracking.

github stars

43

AI-powered SVG generation and editingReal-time progress trackingFull TypeScript support

best for

  • / Designers creating scalable graphics from descriptions
  • / Developers automating SVG generation workflows
  • / Content creators converting images to vector format

capabilities

  • / Generate SVGs from text descriptions
  • / Edit existing SVGs with natural language commands
  • / Convert bitmap images to SVG format
  • / Customize quality settings for conversions
  • / Track progress of operations in real-time

what it does

Connects to SVGMaker API to generate SVG images from text descriptions, edit existing SVGs with natural language, and convert bitmap images to vector format.

about

SVGMaker is a community-built MCP server published by genwavellc that provides AI assistants with tools and capabilities via the Model Context Protocol. SVGMaker is an svg generator and creator that converts photos into vector graphic file types, with editing and real-time It is categorized under ai ml.

how to install

You can install SVGMaker 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

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

readme

SVGMaker MCP Server

A powerful MCP server for generating, editing, and converting SVG images using SVGMaker API.

Website npm version License Build Status npm downloads

🎨 MCP Server in Action

MCP Capabilities Demo

This very illustration came to life through our own SVGMaker MCP server—a living example of AI assistants and vector graphics working in perfect harmony via the Model Context Protocol.

🌟 Highlights

  • 🎨 AI-Powered SVG Generation: Create SVGs from text descriptions
  • ✏️ Smart SVG Editing: Edit existing SVGs with natural language
  • 🔄 Image-to-SVG Conversion: Convert any image to scalable SVG
  • 🔒 Secure File Operations: Built-in path validation and security
  • ⚡ Real-Time Progress: Live updates during operations
  • 📝 Type Safety: Full TypeScript support with type definitions

📋 Table of Contents

💻 Requirements

  • Node.js: Minimum version 18.0.0
    node --version  # Should be >= v18.0.0
    
  • npm: Minimum version 7.0.0
    npm --version   # Should be >= 7.0.0
    
  • Operating Systems:
    • Linux (Ubuntu 20.04+, CentOS 8+)
    • macOS (10.15+)
    • Windows (10+)
  • SVGMaker API key (Get one here)

📦 Package Structure

@genwave/svgmaker-mcp/
├── build/             # Compiled JavaScript files
├── docs/              # Documentation
│   └── api/           # API documentation
├── src/               # Source TypeScript files
│   ├── tools/         # MCP tool implementations
│   ├── services/      # API integration
│   └── utils/         # Utility functions
└── types/             # TypeScript declarations

🚀 Installation

# Using npm
npm install @genwave/svgmaker-mcp

# Using yarn
yarn add @genwave/svgmaker-mcp

Basic Setup

  1. Create .env file:
SVGMAKER_API_KEY="your_api_key_here"
  1. Start the server:
npx svgmaker-mcp

🔌 LLM Integrations

🔌 Claude Desktop

  1. Add to claude_desktop_config.json:
{
  "mcpServers": {
    "svgmaker": {
      "command": "npx",
      "args": ["@genwave/svgmaker-mcp"],
      "transport": "stdio",
      "env": {
        "SVGMAKER_API_KEY": "your_api_key_here"
      }
    }
  }
}
  1. Example Claude prompt:
Generate an SVG of a minimalist mountain landscape:
<mcp>
{
  "server": "svgmaker",
  "tool": "svgmaker_generate",
  "arguments": {
    "prompt": "Minimalist mountain landscape with sun",
    "output_path": "./landscape.svg",
    "quality": "high",
    "aspectRatio": "landscape"
  }
}
</mcp>

🔌 Cursor

Install MCP Server

Or configure manually:

  1. Configure in cursor settings:
{
  "mcpServers": {
    "svgmaker": {
      "type": "local",
      "command": "npx",
      "args": ["@genwave/svgmaker-mcp"],
      "transport": "stdio",
      "env": {
        "SVGMAKER_API_KEY": "your_api_key_here"
      }
    }
  }
}
  1. Example usage in Cursor:
Use svgmaker to edit the logo.svg file and make it more modern:
<mcp>
{
  "server": "svgmaker",
  "tool": "svgmaker_edit",
  "arguments": {
    "input_path": "./logo.svg",
    "prompt": "Make it more modern and minimalist",
    "output_path": "./modern_logo.svg",
    "quality": "high"
  }
}
</mcp>

🔌 Visual Studio Code

<img alt="Install in VS Code (npx)" src="https://img.shields.io/badge/VS_Code-VS_Code?style=flat-square&label=Install%20SVGMaker%20MCP&color=0098FF">

Or configure manually:

  1. Configure in settings.json:
{
  "servers": {
    "svgmaker": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@genwave/svgmaker-mcp"],
      "env": {
        "SVGMAKER_API_KEY": "<your_api_key>"
      }
    }
  }
}
  1. Example usage in VS Code:
Generate a new icon for my app:
<mcp>
{
  "server": "svgmaker",
  "tool": "svgmaker_generate",
  "arguments": {
    "prompt": "Modern app icon with abstract geometric shapes",
    "output_path": "./assets/icon.svg",
    "quality": "high",
    "aspectRatio": "square"
  }
}
</mcp>

🔌 WindSurf

  1. Configure in settings:
{
  "mcpServers": {
    "svgmaker": {
      "command": "npx",
      "args": ["-y", "@genwave/svgmaker-mcp"],
      "env": {
        "SVGMAKER_API_KEY": "<your_api_key>"
      }
    }
  }
}
  1. Example usage in WindSurf:
Convert the company logo to SVG:
<mcp>
{
  "server": "svgmaker",
  "tool": "svgmaker_convert",
  "arguments": {
    "input_path": "./branding/logo.png",
    "output_path": "./branding/vector_logo.svg"
  }
}
</mcp>

🔌 Zed

  1. Configure in settings:
{
  "context_servers": {
    "svgmaker": {
      "command": {
        "path": "npx",
        "args": ["-y", "@genwave/svgmaker-mcp"],
        "env": {
          "SVGMAKER_API_KEY": "<your_api_key>"
        }
      },
      "settings": {}
    }
  }
}
  1. Example usage in Zed:
Edit an existing SVG file:
<mcp>
{
  "server": "svgmaker",
  "tool": "svgmaker_edit",
  "arguments": {
    "input_path": "./diagrams/flowchart.svg",
    "prompt": "Add rounded corners and smooth gradients",
    "output_path": "./diagrams/enhanced_flowchart.svg",
    "quality": "high"
  }
}
</mcp>

🛠️ Available Tools

svgmaker_generate

Generate SVG images from text prompts. Supports style parameters for fine-grained control over the output.

{
  "prompt": "A minimalist mountain landscape with sun",
  "output_path": "/path/to/landscape.svg",
  "quality": "medium",
  "style": "flat",
  "color_mode": "few_colors",
  "composition": "full_scene",
  "background": "transparent"
}

svgmaker_edit

Edit existing SVGs or images with natural language. Supports the same style parameters as generate.

{
  "input_path": "/path/to/input.svg",
  "prompt": "Add a gradient background and make it more vibrant",
  "output_path": "/path/to/enhanced.svg",
  "quality": "high",
  "style": "cartoon",
  "background": "opaque"
}

svgmaker_convert

Convert raster images to SVG using AI-powered vectorization.

{
  "input_path": "/path/to/image.png",
  "output_path": "/path/to/vector.svg"
}

⚙️ Configuration

Environment Variables

VariableDescriptionRequiredDefault
SVGMAKER_API_KEYYour SVGMaker API key✅ Yes-
SVGMMAKER_RATE_LIMIT_RPMAPI rate limit (requests per minute)❌ No2
SVGMAKER_BASE_URLCustom SVGMaker API base URL❌ Nohttps://api.svgmaker.io
SVGMAKER_DEBUGEnable debug logging❌ Nofalse

Debug Logging

The server includes comprehensive logging for debugging and monitoring:

Enable Logging:

# Enable debug logging
SVGMAKER_DEBUG=true npx @genwave/svgmaker-mcp

# Or set NODE_ENV to development
NODE_ENV=development npx @genwave/svgmaker-mcp

Log Files Location:

  • macOS/Linux: ~/.cache/svgmaker-mcp/logs/
  • Windows: %LOCALAPPDATA%/svgmaker-mcp/logs/
  • Fallback: ./logs/ (in project directory)

Log File Format:

mcp-debug-2025-06-04T10-30-45-123Z.log

🔍 Development

Local Setup

  1. Clone and install dependencies:
npm install
  1. Create .env file with your API key
SVGMAKER_API_KEY="your_api_key_here"
  1. Run in development mode:
npm run dev

Testing

Use the MCP Inspector for testing:

npx @modelcontextprotocol/inspector node build/index.js

CI/CD Workflow

This project uses GitHub Actions for continuous integration and deployment:

  1. Continuous Integration

    • Runs on every push to main branch and pull requests
    • Performs linting, type checking, and building
    • Ensures code quality and consistency
  2. Releasing a New Version

    • To release a patch version (bug fixes):
      npm run release:patch
      
    • To release a minor version (new features):
      npm run release:minor
      
    • To release a major version (breaking changes):
      npm run release:major
      
  3. Publishing

    • Automatically publishes to npm when a new version tag is pushed

🔐 Security

  • ✅ Path validation prevents directory traversal
  • ✅ Input sanitization for all parameters
  • ✅ Secure file operation handling
  • ✅ Environment variable protection
  • ✅ Rate limiting support

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.


FAQ

What is the SVGMaker MCP server?
SVGMaker 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 SVGMaker?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

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

  • Piyush G· Sep 9, 2024

    We evaluated SVGMaker against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

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

  • Sakshi Patil· Jul 7, 2024

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

  • Ganesh Mohane· Jun 6, 2024

    I recommend SVGMaker for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

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

  • Dhruvi Jain· Apr 4, 2024

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

  • Rahul Santra· Mar 3, 2024

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

  • Pratham Ware· Feb 2, 2024

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

  • Yash Thakker· Jan 1, 2024

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