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"Resources for CSS and HTML" matching MCP servers:

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    Local-first visual design workspace for AI assistants. Compose wireframes and branded multi-page HTML/CSS documents with live preview, annotations, brand and asset libraries, typed data collections, layout validation, PDF export, and draft-only Gmail handoff.
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    337
    18
    MIT
  • A
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    MCP server for Uiverse.io that lets AI agents browse, search, and fetch open-source UI components (HTML + CSS) directly in their editor. No API key required, it indexes 3,800+ components locally.
    7
    MIT
  • A
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    Scrape any webpage and return clean markdown, HTML, or structured JSON. Bypasses anti-bot protection, renders JavaScript (React/Vue/Angular), supports premium residential proxies and CSS extraction. Works with any MCP client — no local install required.
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    MIT
  • A
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    Dynamic QR code platform for AI agents. Create, customize, and track QR codes without regenerating images. 37 tools covering 11 QR types (URL, vCard, WiFi, event…).
    37
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    MIT
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    An MCP server for rendering common ECharts visualizations from structured tool arguments, exposing per-chart opener tools that map to independent HTML app resources.
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    MIT
  • A
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    Translates design tokens across platforms — extracts from Tailwind/CSS/Figma and generates native themes for Material 3, SwiftUI, and CSS variables with WCAG contrast validation.
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    5
    MIT
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    This server integrates with Mozilla Developer Network (MDN) documentation to suggest CSS properties, check browser support, and provide implementation guidance with user consent mechanisms.
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    4
    MIT
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    MCP Server for accessing W3C/WHATWG/IETF web specifications. Provides AI assistants with access to official web standards data including specifications, WebIDL definitions, CSS properties, and HTML elements.
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    MIT
  • A
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    Enables AI to directly read and analyze Lanhu design drafts and requirement documents to generate HTML, CSS, and structural analyses. It allows users to extract design slices and process prototype pages directly within AI clients.
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    MIT
  • F
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    Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.
    2