"Learning NestJS Framework Knowledge" matching MCP servers:

MCP server with 12 tools for design, UX, conversion, and product knowledge from Frontend Masters courses by Paul Boag and Sarah Drasner, enabling audits, accessibility checks, layout recommendations, and more.

Provides access to Iconify's 200,000+ open source vector icons from 200+ icon sets, enabling search, browsing, and retrieval of icon data with framework usage examples.

Enables AI assistants to build trauma-informed, dyslexia-friendly educational software with specialized tools for accessible UI generation, content review, and multisensory learning activities.

Enables coding agents like Cursor to access Figma design data, fetch layout and styling information, and implement designs in any framework.

Search, inspect and install the 21 free MIT components of Marvelous UI (framework-agnostic Web Components and CSS) and their design tokens into a project. Runs locally over stdio with no network calls.

Provides Claude with queryable knowledge of 300+ visual aesthetics from the Aesthetics Wiki and enables turning that knowledge into design tokens, Tailwind configs, and design briefs.

Transforms HTML into Figma designs using only the user’s design system, ensuring correct component usage or safe fallback to primitives, while continuously learning from each build to improve mapping accuracy and consistency.

Open-source, bidirectional Figma agent for MCP clients — a free alternative to Figma's Dev Mode MCP. Reads designs with high-fidelity grounding and writes back to the canvas: frames, text, auto-layout, styles, variables, and components. 92 tools, no API token, no paid Figma seat.

Provides expert design and marketing guidance for AI coding agents through curated knowledge documents and tools. Covers UI/UX, copywriting, SEO, GEO, and conversion optimization.

Provides deterministic, read-only design knowledge for AI coding agents to help them choose visual directions, plan UI states, and compose design tokens, all without network access.

An intelligent MCP server for Google Stitch that generates production-ready UI from text prompts, with auto-orchestration of design systems, WCAG accessibility, responsive breakpoints, and framework conversion (React, Vue, Svelte).

MCP server that gives LLMs deep knowledge of design systems and tokens, enabling intelligent design evolution, token analysis, and designer-to-developer handoffs.

Maps design components, tokens, and patterns to their code implementations, providing AI coding agents with exact-match resolution across any design tool and framework. Enables agents to reliably discover and reuse existing components across React, Vue, Flutter, SwiftUI, and more.

A Model Context Protocol server that exposes an airline design system as a queryable knowledge base, enabling AI to discover components, find components for use cases, and scaffold prototypes.

Exposes iDRAC design-system knowledge via a single get_component tool, currently returning placeholder data for known components.

A design knowledge MCP server that Claude can query when generating UI, covering eight layers: principles, patterns, content design systems, research methods, service design, brand/visual, business strategy, and design tokens.

tdmcp is an open-source (MIT) Model Context Protocol server for TouchDesigner. You describe a visual in plain language and your AI assistant builds the real node network inside TouchDesigner, checks it for errors, and shows a preview — it ships an embedded operator knowledge base so the model uses real operators instead of guessing. TypeScript codebase, runs locally.

Converts Markdown content into beautifully designed knowledge cards with customizable styles and sizes. Also supports fetching and converting WeChat public account articles to Markdown.

Enables AI assistants to read Lanhu design collaboration content: extracting and analyzing Axure prototype pages, downloading UI designs and slices, and converting design specs into HTML+CSS for implementation. It also provides a shared team message board so multiple AI tools can reuse requirement analyses and knowledge across projects.

Enables LLM agents to generate and validate multi-granularity storyboard assets from text prompts, including 2D SVG motion, 3D Blender depth/blockout, and SDXL ControlNet final images. It also supports vision-based self-correction and a SQLite knowledge database of successful recipes.