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    🎨 AI-powered UI/UX design intelligence - 1519+ curated design resources through MCP | React, Vue, Next.js, Flutter & more
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    132 npm
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    MIT
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    Enables AI agents to browse, search, and read a curated library of 198 UI/UX and animation design skills across 17 categories, distilled from 10 open-source projects, with a progressive 5-step workflow for guidance.
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    665 npm
    MIT
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    Bidirectional MCP bridge enabling AI assistants to draw UI on Figma canvas and read designs back as structured data or code tokens via localhost, requiring Figma Desktop.
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    329 npm
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    Provides Japanese UX conventions as an MCP server to help AI generate correct Japanese UI elements like proper name order, furigana, phone formats, and polite language. It includes tools for form generation, validation, keigo suggestions, and cultural adaptation for developers building Japanese-facing products.
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    39 npm
    MIT
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    Provides comprehensive UI design assistance tools for LLMs, generating color palettes, typography, spacing systems, shadows, design tokens, and more via the MCP protocol.
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    MIT
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    A TypeScript server that enhances AI assistants' capabilities when working with Starwind UI components, providing tools for project initialization, component installation, documentation access, and more.
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    133 npm
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    Enables AI assistants to search, understand, and retrieve UI components from ui-layouts.com through tools like search, documentation, metadata, and source code access.
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    91 npm
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    An MCP server that provides comprehensive UX best practices covering accessibility, usability, UI patterns, design systems, performance, and more, enabling clients to analyze and generate UX-optimized code and recommendations.
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    166 npm
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    Records privacy-preserving receipts for AI-assisted tasks and enables optional onchain reward claiming via AIPOU tokens. Integrates with MCP-compatible clients like Claude and Cursor.
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    Visual CVE audit dashboard for npm, Python, Go, and Rust projects. Scans your project manifests (package-lock.json, requirements.txt, go.sum, Cargo.lock) against OSV.dev live data, opens a browser dashboard for human review, then applies fixes only after explicit confirmation. Supports multi-service monorepos in one command.
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    Enables AI agents to receive a structured verdict on whether a UI component need can be satisfied by existing shadcn/ui or 21st.dev components or requires a custom build, with coverage scoring against real component evidence and a Mobbin reference when needed.
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    254 npm
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    MIT