memoire
Design system MCP server. 20 tools: extract design tokens from any URL, pull from Figma or Penpot, generate React + shadcn/ui components from specs, run WCAG audits, sync tokens bidirectionally.
README
<p align="center"> <img src="assets/authentic-logo.svg" alt="Memoire" width="80" height="80" /> </p>
<h1 align="center">memoire</h1>
<p align="center"> <strong>Extract any website's design system. Generate production React components.</strong><br/> One command. No account. No Figma required. </p>
<p align="center"> <a href="https://www.npmjs.com/package/@sarveshsea/memoire"><img src="https://img.shields.io/npm/v/@sarveshsea/memoire?color=black" alt="npm"></a> <a href="https://github.com/sarveshsea/m-moire/actions/workflows/ci.yml"><img src="https://github.com/sarveshsea/m-moire/actions/workflows/ci.yml/badge.svg" alt="CI"></a> <img src="https://img.shields.io/badge/tests-700%20passing-black" alt="698 tests"> <img src="https://img.shields.io/badge/MCP%20tools-21-black" alt="20 MCP tools"> <a href="https://github.com/sarveshsea/m-moire/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-black.svg" alt="MIT"></a> <a href="https://glama.ai/mcp/servers/sarveshsea/m-moire"><img src="https://glama.ai/mcp/servers/sarveshsea/m-moire/badges/score.svg?v=2" alt="MCP server score"></a> </p>
<p align="center"> <a href="https://glama.ai/mcp/servers/sarveshsea/m-moire"> <img src="https://glama.ai/mcp/servers/sarveshsea/m-moire/badges/card.svg?v=2" alt="m-moire MCP server" width="400" /> </a> </p>
Try it now
npx @sarveshsea/memoire design-doc https://stripe.com
Extracts colors, typography, spacing, shadows, and component patterns from any public URL. Outputs a DESIGN.md with a Tailwind config sketch. 10 seconds. Zero config.
<p align="center"> <img src="assets/demo.gif" alt="memoire extracting a design system from a URL" width="720" /> </p>
What you get
| Input | Output |
|---|---|
| Any public URL | DESIGN.md with full token inventory + Tailwind config |
| Figma file (REST or plugin) | Design tokens, components, styles |
| Penpot file | Same tokens, same pipeline |
| JSON specs | React + TypeScript + Tailwind components (shadcn/ui) |
| Generated components | Storybook stories + shadcn registry server |
npm i -g @sarveshsea/memoire
memi design-doc https://linear.app # extract any site's design system
memi go # figma -> tokens -> specs -> components -> preview
memi go --rest # same thing, no figma desktop needed
memi go --penpot # same thing, from penpot
memi tokens # export as CSS / Tailwind / JSON / Style Dictionary
Use with Claude Code / Cursor
Memoire is an MCP server with 21 tools. Give your AI assistant direct access to your design system.
memi mcp config --install # writes .mcp.json, done
Or add manually to .mcp.json:
{
"mcpServers": {
"memoire": {
"command": "memi",
"args": ["mcp", "start"]
}
}
}
Tools include: pull_design_system, generate_code, create_spec, get_tokens, compose, design_doc, run_audit, capture_screenshot, analyze_design, and 11 more.
Full command reference
<details> <summary><strong>Core workflow</strong></summary>
| Command | What it does |
|---|---|
memi setup |
Full onboarding: token, file, plugin, bridge, MCP config, test pull |
memi init |
Initialize workspace with starter specs |
memi connect |
Start Figma bridge (auto-discovers plugin on ports 9223-9232) |
memi pull |
Extract tokens, components, styles from Figma |
memi pull --rest |
Pull via REST API -- no plugin, no Figma Desktop |
memi pull --penpot |
Pull from Penpot (needs PENPOT_TOKEN + PENPOT_FILE_ID) |
memi spec <type> <name> |
Create a component, page, or dataviz spec |
memi generate [name] |
Generate shadcn/ui code + Storybook stories from specs |
memi generate --no-stories |
Generate without Storybook stories |
memi preview |
Start preview gallery + shadcn registry server |
memi go |
Full pipeline in one command |
memi export |
Export generated code into your project |
memi tokens |
Export tokens as CSS / Tailwind / JSON / Style Dictionary (W3C DTCG) |
memi validate |
Validate all specs against schemas |
</details>
<details> <summary><strong>Design extraction</strong></summary>
| Command | What it does |
|---|---|
memi design-doc <url> |
Extract design system from any URL into DESIGN.md |
memi design-doc <url> --spec |
Also write a DesignSpec JSON for codegen |
memi extract <url> |
Alias for design-doc |
</details>
<details> <summary><strong>Sync, agents, research</strong></summary>
| Command | What it does |
|---|---|
memi sync |
Full sync: Figma + specs + code |
memi sync --live |
Watch and sync continuously |
memi compose "<intent>" |
Agent orchestrator: classify, plan, execute |
memi agent spawn <role> |
Spawn a persistent agent worker |
memi research from-file <path> |
Process Excel/CSV into research |
memi research synthesize |
Synthesize themes and personas |
memi daemon start |
Start daemon with reactive pipeline |
</details>
<details> <summary><strong>Diagnostics</strong></summary>
| Command | What it does |
|---|---|
memi status |
Project status overview |
memi doctor |
Health check: project, plugin, bridge |
memi dashboard |
Launch monitoring dashboard |
memi audit |
Design system audit (WCAG, unused specs) |
All commands support --json for structured output.
</details>
Spec-first workflow
Every component starts as a JSON spec before code is generated:
{
"name": "MetricCard",
"type": "component",
"level": "molecule",
"shadcnBase": ["Card", "Badge"],
"props": { "title": "string", "value": "string", "trend": "string?" },
"variants": ["default", "compact"]
}
Specs are validated with Zod schemas. Components follow Atomic Design (atom, molecule, organism, template, page).
Architecture
src/
engine/ Core orchestrator, registry, sync, pipeline
figma/ WebSocket bridge + REST client + Penpot client
agents/ Intent classifier, plan builder, task queue
mcp/ MCP server (21 tools, 3 resources, stdio)
codegen/ shadcn/ui mapper, Storybook, dataviz, pages
research/ Research engine (Excel, stickies, web)
specs/ Spec types, Zod schemas, 62-component catalog
preview/ Preview gallery, API server, shadcn registry
notes/ Downloadable skill packs
commands/ 28 CLI commands
plugin/ Figma plugin (Widget V2)
Links
memoire.cv -- Changelog -- MCP docs -- Notes
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。