by genwavellc
SVGMaker is an svg generator and creator that converts photos into vector graphic file types, with editing and real-time
Connects to SVGMaker API to generate SVG images from text descriptions, edit existing SVGs with natural language, and convert bitmap images to vector format.
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.
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.
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.
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
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
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
Share your MCP server with the developer community
According to our notes, SVGMaker benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
According to our notes, SVGMaker benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We wired SVGMaker into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
We wired SVGMaker into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
SVGMaker is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
SVGMaker is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We evaluated SVGMaker against two servers with overlapping tools; this profile had the clearer scope statement.
I recommend SVGMaker for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Strong directory entry: SVGMaker surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Strong directory entry: SVGMaker surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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A powerful MCP server for generating, editing, and converting SVG images using SVGMaker API.
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.
node --version # Should be >= v18.0.0
npm --version # Should be >= 7.0.0
@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
# Using npm
npm install @genwave/svgmaker-mcp
# Using yarn
yarn add @genwave/svgmaker-mcp
SVGMAKER_API_KEY="your_api_key_here"
npx svgmaker-mcp
{
"mcpServers": {
"svgmaker": {
"command": "npx",
"args": ["@genwave/svgmaker-mcp"],
"transport": "stdio",
"env": {
"SVGMAKER_API_KEY": "your_api_key_here"
}
}
}
}
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>
Or configure manually:
{
"mcpServers": {
"svgmaker": {
"type": "local",
"command": "npx",
"args": ["@genwave/svgmaker-mcp"],
"transport": "stdio",
"env": {
"SVGMAKER_API_KEY": "your_api_key_here"
}
}
}
}
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>
Or configure manually:
{
"servers": {
"svgmaker": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@genwave/svgmaker-mcp"],
"env": {
"SVGMAKER_API_KEY": "<your_api_key>"
}
}
}
}
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>
{
"mcpServers": {
"svgmaker": {
"command": "npx",
"args": ["-y", "@genwave/svgmaker-mcp"],
"env": {
"SVGMAKER_API_KEY": "<your_api_key>"
}
}
}
}
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>
{
"context_servers": {
"svgmaker": {
"command": {
"path": "npx",
"args": ["-y", "@genwave/svgmaker-mcp"],
"env": {
"SVGMAKER_API_KEY": "<your_api_key>"
}
},
"settings": {}
}
}
}
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>
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"
}
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"
}
Convert raster images to SVG using AI-powered vectorization.
{
"input_path": "/path/to/image.png",
"output_path": "/path/to/vector.svg"
}
| Variable | Description | Required | Default |
|---|---|---|---|
SVGMAKER_API_KEY | Your SVGMaker API key | ✅ Yes | - |
SVGMMAKER_RATE_LIMIT_RPM | API rate limit (requests per minute) | ❌ No | 2 |
SVGMAKER_BASE_URL | Custom SVGMaker API base URL | ❌ No | https://api.svgmaker.io |
SVGMAKER_DEBUG | Enable debug logging | ❌ No | false |
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:
~/.cache/svgmaker-mcp/logs/%LOCALAPPDATA%/svgmaker-mcp/logs/./logs/ (in project directory)Log File Format:
mcp-debug-2025-06-04T10-30-45-123Z.log
npm install
SVGMAKER_API_KEY="your_api_key_here"
npm run dev
Use the MCP Inspector for testing:
npx @modelcontextprotocol/inspector node build/index.js
This project uses GitHub Actions for continuous integration and deployment:
Continuous Integration
Releasing a New Version
npm run release:patch
npm run release:minor
npm run release:major
Publishing
We welcome contributions! Please see our Contributing Guide for details.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ 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.