arikusi/nakkas
by Various
MCP server that turns AI into an SVG artist
MCP
arikusi/nakkas
Added 1 June 2026
Overview
A Model Context Protocol server that enables AI agents to generate SVG graphics. It exposes tools for creating, editing, and exporting vector illustrations through a standardized interface.
Best for
Best for
Developers building AI-powered design tools or needing automated SVG generation
Use cases
- Generate custom SVG icons and illustrations from natural language prompts
- Edit existing SVG files programmatically via AI agents
- Export vector graphics in multiple formats for web or print use
How to use
Install
claude mcp add nakkas npx nakkas@latest Tools exposed
render_svgradial-grouparc-groupgrid-groupscatter-grouppath-groupdrop-shadowhue-rotatechromatic-aberrationinner-shadow
Tested with
Claude Desktop, Claude Code, Cursor
Example client config
{\n "mcpServers": {\n "nakkas": {\n "command": "npx",\n "args": ["-y", "nakkas@latest"]\n }\n }\n} Notes
A Model Context Protocol server that enables AI agents to generate SVG graphics. It exposes tools for creating, editing, and exporting vector illustrations through a standardized interface.
9 stars on GitHub. Last updated 2026-04-06. Licensed MIT.
Use cases
- Generate custom SVG icons and illustrations from natural language prompts
- Edit existing SVG files programmatically via AI agents
- Export vector graphics in multiple formats for web or print use
Pros
- Leverages the MCP standard for easy integration with AI assistants
- Written in TypeScript with good type safety and developer ergonomics
- Lightweight and focused on a single, well-defined task
Cons
- Limited to SVG output, not suitable for raster or 3D graphics
- Depends on the underlying AI model’s ability to understand vector art concepts
- Small community and limited documentation due to early stage
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Leverages the MCP standard for easy integration with AI assistants
- Written in TypeScript with good type safety and developer ergonomics
- Lightweight and focused on a single, well-defined task
Cons
- Limited to SVG output, not suitable for raster or 3D graphics
- Depends on the underlying AI model's ability to understand vector art concepts
- Small community and limited documentation due to early stage
Pairs with
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