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GenWaveLLC/svgmaker-mcp

by Various

Model Context Protocol server for SVGMaker - AI-powered SVG generation and editing. Seamlessly integrate SVG creation into AI workflows.

G

MCP

GenWaveLLC/svgmaker-mcp

Added 1 June 2026

Overview

A Model Context Protocol server that wraps the SVGMaker library to provide SVG generation and editing capabilities to MCP-compatible AI agents. It allows agents to create and modify scalable vector graphics programmatically through standardised tool calls.

Best for

Best for
Developers who want to add SVG generation capabilities to MCP-based agent workflows without building a custom integration.

Use cases

  • Generate SVG icons or illustrations from natural language prompts
  • Edit existing SVG files (resize, recolor, restructure) via agent commands
  • Integrate SVG creation into chat-based AI workflows for rapid prototyping

Notes

A Model Context Protocol server that wraps the SVGMaker library to provide SVG generation and editing capabilities to MCP-compatible AI agents. It allows agents to create and modify scalable vector graphics programmatically through standardised tool calls.

73 stars on GitHub. Last updated 2026-05-22. Licensed MIT.

Use cases

  • Generate SVG icons or illustrations from natural language prompts
  • Edit existing SVG files (resize, recolor, restructure) via agent commands
  • Integrate SVG creation into chat-based AI workflows for rapid prototyping

Pros

  • Built on the MCP standard, enabling drop-in use with many AI hosts
  • Written in TypeScript, offering type safety and broad ecosystem compatibility
  • Open source with a permissive license for community contributions

Cons

  • Relatively small user base (73 stars) suggests limited real-world testing
  • Depends entirely on the SVGMaker library, which may lack advanced editing features
  • Documentation and examples are sparse, increasing the learning curve

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Built on the MCP standard, enabling drop-in use with many AI hosts
  • Written in TypeScript, offering type safety and broad ecosystem compatibility
  • Open source with a permissive license for community contributions

Cons

  • Relatively small user base (73 stars) suggests limited real-world testing
  • Depends entirely on the SVGMaker library, which may lack advanced editing features
  • Documentation and examples are sparse, increasing the learning curve