Nakkas MCP Server Generates Animated SVGs from AI Descriptions

Nakkas is an MCP server that enables AI to create animated SVGs from scratch. You describe what you want, and the AI constructs the full configuration including shapes, gradients, animations, and filters, with the server rendering clean animated SVG output.
Key Features and Capabilities
According to the source, Nakkas can generate:
- Animated logos, loading spinners, and data visualizations
- Scatter fields, radial patterns, and grid layouts
- Parametric curves including rose, spiral, heart, and superformula shapes
- 15 filter presets such as glow, neon, glitch, and chromatic aberration
- CSS @keyframes + SMIL animations with zero JavaScript
- Works anywhere SVG renders
Getting Started
You can install and run Nakkas using:
npx nakkas@latestThe tool is available via npm at https://www.npmjs.com/package/nakkas and the source code is hosted on GitHub at https://github.com/arikusi/nakkas.
The creator is seeking feedback and encourages users to share examples in the GitHub discussions.
📖 Read the full source: r/ClaudeAI
👀 See Also

Exploring Clawe: Open-source Multi-agent Coordination System
Clawe is an open-source tool allowing for efficient multi-agent coordination, offering features like scheduling, task management, and real-time notifications.

Terrarium: Open-Source Sandbox for Agentic Environments with Time Machine Rewind
A versatile sandboxing solution for running multiple AI agents securely on any VPS or cloud. Features isolated worlds, reverse-proxy management, GUIs, and a time machine to rewind container state.

OpenLobster: Self-Hosted AI Agent in Go with 30MB RAM Footprint
OpenLobster is a self-hosted AI assistant written in Go that runs as a single binary with 30MB RAM usage and 200ms cold start. It supports multiple LLM providers including Ollama, OpenRouter, and any OpenAI-compatible endpoint, with memory stored in a graph database.

Infracost cuts Claude token usage 79% by redesigning CLI for AI agents
Infracost redesigned its CLI for AI agent callers, cutting Claude output tokens by 79% and API cost by 67% vs a bare-Claude baseline. Key moves: predicate pushdown into the CLI and a token-efficient output format.