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Supports UI/UX, design systems, SEO, accessibility, and marketing workflows.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.HalidSaglam/saglitzdesign-mcp" MCP server from askskill: Run: claude mcp add 'io-github-halidsaglam-saglitzdesign-mcp' -- npx -y saglitzdesign-mcp
Please review this login page from a UI/UX perspective. Identify issues in information hierarchy, form experience, error messaging, and mobile responsiveness, then suggest improvements.
A list of UX issues with actionable improvement recommendations.
Help me organize this product’s design language. Summarize the core rules for color, typography, spacing, buttons, and forms, and identify what should become design tokens.
A design language summary with token candidates for structured management.
For this landing page content, give me optimization recommendations that cover both SEO/GEO and accessibility, including heading structure, keyword phrasing, alt text, and readability.
A combined optimization checklist for search performance and accessibility.
Designers can use it to structure UI/UX guidance, design language, and tokens when consolidating product standards.
Marketers or product managers can use it to improve websites and landing pages with SEO/GEO-oriented recommendations while keeping content readable and conversion-focused.
During design reviews or pre-launch checks, teams can use it to surface accessibility-related issues in content and structure.
Based on the description, it targets design and marketing workflows, covering UI/UX, design languages, SEO/GEO, design tokens, accessibility, and recipes.
It is best suited for designers, marketers, and product managers. Anyone working on design systems, page optimization, or accessibility checks may benefit from it.
The provided materials do not include installation steps, runtime details, or key requirements. Please see the source repository for setup and prerequisites.
Provides MCP tools for contrast checks, text counting, image conversion, and JSON-LD.
Gives AI coding agents queryable design system guidance for accurate implementation.
End-to-end frontend design tools for generating, reviewing, testing, and exporting UI.
Discover design system components and generate implementation-ready frontend code automatically.
Search, read, and discover related design system components via MCP.
Analyze Lanhu designs and Zentao bug reports to surface issues and improvements.