Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者提供的说明(英文原文)
Agent-native UI/UX design validation: journey completeness, state coverage, and WCAG checks.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
UXLOOM_PROJECT你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"uxloom": {
"command": "npx",
"args": [
"-y",
"uxloom"
],
"env": {
"UXLOOM_PROJECT": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add uxloom --env UXLOOM_PROJECT=your-value -- npx -y uxloom运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"uxloom": {
"command": "npx",
"args": [
"-y",
"uxloom"
],
"env": {
"UXLOOM_PROJECT": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"uxloom": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"uxloom"
],
"env": {
"UXLOOM_PROJECT": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
UXLOOM_PROJECT env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 uxloom-dev 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.14.0)于3个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Your generator gave you 6 screens. UXLoom proves you're missing 9 states.
AI generators (v0, Lovable, Figma Make, Claude) produce happy-path screens. UXLoom is the critic layer: it models user journeys as state machines, treats screens as nodes with state contracts, and mechanically proves what's missing before a line of production code exists — unreachable screens, dead ends, missing error/empty/loading states, WCAG contrast failures, undersized touch targets, and labels that will overflow under localization.
Agent-native by design: the interface is an MCP server (works with Claude Code, Codex, and any MCP client), with Agent Skills included.
Deterministic by design: same input, byte-identical report — benchmarked (packages/bench) at 1.000 precision/recall on a seeded defect catalog, SHA-256-stable across processes, 1000 screens in under 5ms. That's what lets design completeness gate CI, where an LLM opinion can't.
Website: uxloom.dev · npm: uxloom · MCP registry: io.github.uxloom-dev/uxloom ·
| Package | What it is |
|---|---|
@uxloom/journeygraph | The open design-as-data format: journeys as state machines, screens as nodes with required states |
@uxloom/critics | The validators: journey completeness, state coverage, WCAG contrast, touch targets, text expansion |
uxloom | The MCP server + Agent Skills — the interface agents use |
New here? Start with the [Quickstart](QUICKSTART.md) — prerequisites, the Claude Code walkthrough, what to say to your agent, and troubleshooting.
# Claude Code
claude mcp add uxloom -- npx -y uxloom
codex mcp add uxloom -- npx -y uxloom
The project file (uxloom.project.json) lives in your workspace and belongs in git — the design is data, versioned next to the code it specifies.
npx uxloom init # one-command setup: MCP config + agent skill + starter file
npx uxloom preview # live mocks (themed, commentable, EDITABLE in the browser) npx uxloom export # shareable HTML — plus --svg (Figma/Penpot import; add
npx uxloom check # design completeness — exit 1 on errors, CI-ready npx uxloom audit # implementation drift — web AND native (Swift/Kotlin/
npx uxloom diff # human-readable design diffs for PR review
Evidence-based design: every decision in the contract can carry its rationale — reasoning, rejected alternatives with pros/cons, sources, confidence — enforced by the critics once adopted, iterated through a bounded design_review loop (max 3 rounds), and shown to stakeholders in the preview's evidence panel (ⓘ) and exports. The design doesn't just validate; it argues its case.
Agent-addressable comments: a reviewer drops a pinned comment in the preview and clicks "→ agent". The comment becomes a work item any Gen-AI model can read with full context — comment_context returns the pinned layout block, the screen contract, the journey references, and the current findings for that screen — act on, and resolve back into the preview with a note. One click from feedback to addressed.
CI-native: check and audit take --json, --sarif (GitHub code scanning), and --github (inline PR annotations). Brownfield-ready: --update-baseline freezes existing findings so only *new* drift blocks; uxloom.config.json tunes thresholds to your accessibility bar. Full documentation: uxloom.dev/docs.html.
Add it to CI and a happy-path-only design can never merge:
- run: npx uxloom check design/uxloom.project.json
Workflow (also shipped as a skill in packages/mcp-server/skills/): project_init → brief_start/brief_answer → journey_define → screen_register → project_validate → fix → repeat until zero errors → coverage_report.
tools/dogfood.mjs drives the real MCP server through three products, twice each: screens as a happy-path generator hands them over, then repaired using the validation report. Artifacts in examples/.
| Product | Generated (happy-path) | Repaired |
|---|---|---|
shopmweb — e-commerce checkout (mWeb + Android) | 9 errors, 6 warnings | 0 / 0 |
taskflow — SaaS signup/onboarding (web) | 1 error, 6 warnings | 0 / 0 |
ridenow — ride booking (iOS + Android, offline-heavy) | 3 errors, 7 warnings | 0 / 0 |
Caught: an unreachable promo screen, dead-end verification states, five undesigned payment/error states, a 2.4:1 contrast button, a 40px touch target on Android, a checkout label that breaks in German, and three products' worth of missing offline states. Zero errors *and zero warnings* is reachable honestly — screens declare documented exemptions where a baseline state genuinely cannot apply, and contradictory exemptions are flagged.
npm install
npm run typecheck npm test
Released and maintained: on npm and the official MCP registry, with the benchmark scorecard published in every GitHub release. The JourneyGraph format (formatVersion: "0.1") may evolve until 1.0; releases follow RELEASING.md — every surface is drift-checked in CI.
MIT