memoire

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.

Category
Visit Server

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

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured