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aesthetics-mcp

aesthetics-mcp

A Model Context Protocol server that gives Claude knowledge of 1135+ named visual aesthetics from the Aesthetics Wiki. Use it to generate CSS tokens, Tailwind configs, design briefs, and UI components grounded in real aesthetic traditions.

Prerequisites

  • Node.js 18+

  • Claude Code (CLI, desktop app, or IDE extension)

Related MCP server: figma-mcp-server

Install

git clone https://github.com/InfiniteInsight/aesthetics-mcp.git
cd aesthetics-mcp
npm install
npm run setup

Then restart Claude Code. The MCP server and aesthetics skill are now active.

The database ships pre-scraped and pre-embedded — no scraping or model download needed on first run. The embedding model (~23MB) downloads on the first suggest_aesthetics call.

Usage

The skill activates automatically on design-related requests. You can also trigger it directly:

Intent

Example

Named aesthetic

"make it Vaporwave"

Vibe description

"dark moody academic candlelight"

Project description

"a meditation app, calm but not clinical"

Random inspiration

"pick a random aesthetic for me"

Color-first

"find aesthetics that use black and gold"

Explore

"what aesthetics are related to Dark Academia?"

MCP Tools

Tool

Description

get_aesthetic

Full details + wiki text for a named aesthetic

search_aesthetics

FTS keyword search across all 1135+ aesthetics

suggest_aesthetics

Semantic similarity search from a project description

list_aesthetics

Browse all aesthetics, optionally filtered by category

random_aesthetic

Random pick, optionally filtered by category

search_by_color

Find aesthetics by color name (e.g. "burgundy", "earth tones")

list_categories

All 66 distinct aesthetic categories

find_related

Resolve an aesthetic's related/adjacent neighbors

check_db_staleness

How recently the database was last scraped

Re-scraping

The bundled database was scraped in June 2026. To refresh it:

npm run scrape                        # re-scrapes all 1135 aesthetics (~30 min)
node src/db/migrate-embeddings.js     # re-computes semantic embeddings (~5 min)

Development

npm test          # run all 63 tests
npm run setup     # re-run after pulling changes to update skill + MCP path

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