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)
Resolves Tailwind CSS design tokens and validates utility classes against the local project config.
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。
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": {
"tailwind-context-resolver": {
"command": "npx",
"args": [
"-y",
"tailwind-context-resolver-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add tailwind-context-resolver -- npx -y tailwind-context-resolver-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"tailwind-context-resolver": {
"command": "npx",
"args": [
"-y",
"tailwind-context-resolver-mcp"
]
}
}
}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": {
"tailwind-context-resolver": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"tailwind-context-resolver-mcp"
]
}
}
}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。
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 vola-trebla 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(0.2.0)于6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。
An MCP server that loads your project's tailwind.config.ts/js and exposes its actual design system to AI agents — so they stop hallucinating class names.
AI agents generate Tailwind classes based on training data — the default Tailwind docs. Your project is not the default docs.
You have a custom color palette. A non-standard spacing scale. Maybe a prefix like tw-. Brand tokens like bg-brand-primary. The agent doesn't know any of this. It guesses.
The result:
// Agent confidently generates this:
// Your project has: // - bg-brand-primary (not bg-primary-500) // - no "text-brand" token // - spacing.18 = 4.5rem (ok actually) // - no "flex-center" utility // - no "tw-" prefix
The agent can't validate what it writes because it has no access to your resolved config. It's working from memory of the default theme — not yours.
This MCP server runs the Tailwind resolver locally and gives agents a typed, queryable interface to your actual config. Before writing a component, the agent can ask:
p-18 a valid spacing value here?"bg-brand-primary flex grid a valid class string?"resolve_theme_tokensQuery any namespace in the resolved Tailwind theme. Returns all design tokens as flat key-value pairs.
namespace: "colors.brand" → { primary: "#3b82f6", secondary: "#8b5cf6", danger: "#ef4444" }
namespace: "spacing" → { "1": "0.25rem", "2": "0.5rem", "18": "4.5rem", ... } namespace: "fontFamily" → { sans: ["Inter", "sans-serif"], mono: [...] }
Use before generating components to discover what tokens actually exist.
validate_class_stringValidates a Tailwind className string against the project's resolved config. Returns valid classes, invalid (hallucinated) classes, and conflict warnings.
{
"valid_classes": ["bg-brand-primary", "text-white", "p-4", "hover:bg-brand-secondary", "flex"], "invalid_classes": ["bg-fake-token", "text-brand"], "warnings": ["Conflicting multiple layout models: flex, grid"], "config_prefix": "" }
Use to catch hallucinated design tokens before writing code.
detect_css_conflictsDetects conflicting Tailwind utilities — e.g. flex + grid, or absolute + fixed on the same element.
{
"conflicts": [{ "classes": ["flex", "grid"], "reason": "multiple layout models" }], "has_conflicts": true }
get_config_summaryReturns a compact overview: Tailwind version, prefix, which theme sections are customized, active plugins.
{
"tailwind_version": "3.4.19", "prefix": "", "theme_extensions": ["colors", "spacing", "fontFamily"], "total_colors": 142, "total_spacing": 34, "plugins": ["@tailwindcss/forms"] }
Use first to understand the project's design system before querying specific tokens.
Add to your claude_desktop_config.json:
{
"mcpServers": { "tailwind-context-resolver": { "command": "npx", "args": ["-y", "tailwind-context-resolver-mcp"] } } }
{
"tailwind-context-resolver": { "command": "npx", "args": ["-y", "tailwind-context-resolver-mcp"] } }
tailwind.config.js or tailwind.config.ts in your projectThe server uses the same config loading strategy as the Tailwind CLI:
tailwind.config.ts at runtime — no ts-node requiredbg-brand-primary maps to an actual colors.brand.primary token — without running the full PostCSS/JIT pipelineThis approach is fast, stable, and works with any Tailwind v3 project without additional configuration.
1. get_config_summary → understand the project's design system
Built alongside:
MIT