gulim-fonts
gulim-fonts MCP server recommends Korean and English fonts using 12-dimensional mood vectors and pgvector similarity search across 999+ fonts. It enables keyword-based matching, design guide generation, font browsing, detail lookup, and image mood analysis. UI/UX designers, frontend developers, and content creators use it to match fonts to project moods or images.
Overview
The gulim-fonts MCP server delivers AI-powered font recommendations for Korean and English typography. It leverages 12-dimensional mood vectors stored in a pgvector database with similarity search over more than 999 fonts, enabling precise matches based on semantic descriptors.
Key Capabilities
- keyword_font_matching: Finds fonts by parsing keywords into mood vectors for similarity ranking.
- design_guide_generation: Produces tailored guidelines on font pairing, sizing, and usage for selected fonts.
- font_browsing: Queries and lists fonts filtered by categories, languages, or mood attributes.
- font_detail_lookup: Retrieves metadata like glyph coverage, licensing, and download links for specific fonts.
- image_mood_analysis: Analyzes uploaded images to extract mood vectors and recommend matching fonts.
Use Cases
- A UI/UX designer inputs project keywords like 'modern serene' via keyword_font_matching to get top Korean font recommendations for app interfaces.
- Frontend developers use image_mood_analysis on mockups to suggest English fonts aligning with visual tones.
- Content creators run font_browsing for Hangeul-compatible fonts, then design_guide_generation for web typography rules.
- Teams lookup details with font_detail_lookup to ensure licensing compliance before integration.
Who This Is For
UI/UX designers needing mood-aligned fonts, frontend developers integrating typography APIs, graphic designers handling bilingual projects, and content teams automating font selection in tools like Figma or web builders.