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.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
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.
🎨 MCP Server in Action
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
- Installation
- Quick Start
- LLM Integrations
- Available Tools
- Configuration
- Development
- Contributing
💻 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
- Create .env file:
SVGMAKER_API_KEY="your_api_key_here"
- Start the server:
npx svgmaker-mcp
🔌 LLM Integrations
🔌 Claude Desktop
- Add to claude_desktop_config.json:
{
"mcpServers": {
"svgmaker": {
"command": "npx",
"args": ["@genwave/svgmaker-mcp"],
"transport": "stdio",
"env": {
"SVGMAKER_API_KEY": "your_api_key_here"
}
}
}
}
- 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
Or configure manually:
- Configure in cursor settings:
{
"mcpServers": {
"svgmaker": {
"type": "local",
"command": "npx",
"args": ["@genwave/svgmaker-mcp"],
"transport": "stdio",
"env": {
"SVGMAKER_API_KEY": "your_api_key_here"
}
}
}
}
- 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
Or configure manually:
- Configure in settings.json:
{
"servers": {
"svgmaker": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@genwave/svgmaker-mcp"],
"env": {
"SVGMAKER_API_KEY": "<your_api_key>"
}
}
}
}
- 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
- Configure in settings:
{
"mcpServers": {
"svgmaker": {
"command": "npx",
"args": ["-y", "@genwave/svgmaker-mcp"],
"env": {
"SVGMAKER_API_KEY": "<your_api_key>"
}
}
}
}
- 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
- Configure in settings:
{
"context_servers": {
"svgmaker": {
"command": {
"path": "npx",
"args": ["-y", "@genwave/svgmaker-mcp"],
"env": {
"SVGMAKER_API_KEY": "<your_api_key>"
}
},
"settings": {}
}
}
}
- 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
| 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 |
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
- Clone and install dependencies:
npm install
- Create .env file with your API key
SVGMAKER_API_KEY="your_api_key_here"
- 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:
-
Continuous Integration
- Runs on every push to main branch and pull requests
- Performs linting, type checking, and building
- Ensures code quality and consistency
-
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
- To release a patch version (bug fixes):
-
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 27 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.
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.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 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
4.5★★★★★27 reviews- ★★★★★Nikhil Khanna· Dec 28, 2024
According to our notes, SVGMaker benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Chaitanya Patil· Dec 8, 2024
According to our notes, SVGMaker benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Piyush G· Nov 27, 2024
We wired SVGMaker into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★James Thompson· Nov 19, 2024
We wired SVGMaker into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Shikha Mishra· Oct 18, 2024
SVGMaker is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★James Gupta· Oct 10, 2024
SVGMaker is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Omar Tandon· Sep 21, 2024
We evaluated SVGMaker against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Rahul Santra· Sep 1, 2024
I recommend SVGMaker for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Hiroshi Li· Sep 1, 2024
Strong directory entry: SVGMaker surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Pratham Ware· Aug 20, 2024
Strong directory entry: SVGMaker surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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