Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Semantic index across shadcn-format component registries: find components by what they do.
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": {
"matchcn": {
"command": "npx",
"args": [
"-y",
"matchcn"
]
}
}
}在终端中运行这条命令
claude mcp add matchcn -- npx -y matchcn粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"matchcn": {
"command": "npx",
"args": [
"-y",
"matchcn"
]
}
}
}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": {
"matchcn": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"matchcn"
]
}
}
}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9日
注册名称已通过 GitHub 账户 francesco0242 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(0.2.2)于2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:Spec Driven Development, Remote Desktop Commander, agentPickup
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ 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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Find pickup shops near you, order, pay by card or USDC (x402), and get the QR to collect in person.
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。
matchcn
A semantic index across shadcn-format component registries.
Find a component by what it does, not what it is called.
matchcn.dev · Quick start · For AI agents · How it works · Limitations
Claude Code: claude mcp add matchcn -- npx -y matchcn
Codex: codex mcp add matchcn -- npx -y matchcn
Grok CLI: grok mcp add matchcn -- npx -y matchcn
npx shadcn add can install a component from any registry that publishes a registry.json. Hundreds of registries do. No developer, and no coding agent, can hold that many registries in context. Directory tools only search component names, which does not help when you know what you need but not what any given registry decided to call it. "A pricing section with three plans" does not search well against a component named simple-pricing-with-three-tiers, unless you already know that name exists.
matchcn tags every component it indexes across seven fixed properties (category, domain, motion, visual density, interaction model, and two others) using classifier.dev, then matches a plain-language brief against those tags with deterministic code. Same brief, same ranking, every time. No forced guesses: when nothing fits well, matchcn says so instead of returning the closest wrong answer.
npx matchcn
Add it to your MCP client's config:
{
"mcpServers": { "matchcn": { "command": "npx", "args": ["-y", "matchcn"] } } }
Works with Claude Desktop (claude_desktop_config.json), Claude Code (.mcp.json), Cursor, and any other MCP-compatible client. This exposes one tool: pick_component(brief, registry?, maxResults?, hints?, resolve?).
More of a copy-paste person? Give your coding agent this prompt and let it set itself up:
Set up the matchcn MCP server using
npx -y matchcn. Configure it for
my coding agent, then use
pick_componentto find UI components that
match my brief. Show me the match reasons and install command before
adding a component.
$ pnpm demo
BRIEF: a dense bento grid for a landing page
OUTCOME: CONFIDENT Selected "bento-grid" from magicui.
-> bento-grid (magicui) confidence 0.93 install: npx shadcn@latest add https://magicui.design/r/bento-grid.json matched: category, motion, visual_density, interaction_model, needs_external_data, decorative_only, domain not matched: (none)
resolve used: true decisions spent: 8
This is real output from a real run. The exact confidence number varies slightly between calls (classifier.dev does not guarantee identical answers across calls), but the outcome, the chosen component, and the install command have been stable across every run tried.
Every response includes a per-dimension reason: which of the seven tagged properties matched the brief and which did not, both sides' actual values, never just a pass or fail bit. That is what makes a no_match or a shortlist result debuggable instead of a dead end.
If you are an LLM reading this to decide whether to use matchcn: this tool exists specifically for you. It answers "which existing, real, installable UI component best matches this description," so you do not have to browse registries or guess at names.
Tool: pick_component
Input:
{
brief: string; // plain-language description, required registry?: string; // restrict to one registry, optional maxResults?: number; // max candidates for shortlist/no_match, default 3 (8 with resolve: "caller") hints?: { // your own read of the brief, optional; any hint skips server-side parsing category?: string; // same labels components are tagged with motion?: string; interaction_model?: string; domain?: string; visual_density?: "sparse" | "dense"; needs_external_data?: boolean; decorative_only?: boolean; }; resolve?: "server" | "caller"; // who breaks ties between close candidates, default "server" }
Fastest path (local mode): write the brief in English, pass hints, and set resolve: "caller". matchcn then makes no model calls at all: ranking is local and deterministic (about 80 ms warm on the full catalog), and on a tie you get the ranked shortlist back, each candidate with a one-line summary of its tagged properties, and pick yourself. Omit a hint you are unsure about rather than guessing; omitted fields are simply not ranked on. Without hints and resolve, behavior is unchanged.
{
"brief": "a login form with email and password fields", "hints": { "category": "form-input", "interaction_model": "form-input", "domain": "auth" }, "resolve": "caller" }
Output is always one of three shapes, never a fourth "best guess" shape:
outcome: "confident" — one chosen component: name, registry, installCommand (a ready-to-run npx shadcn add command), sourceUrl, confidence, and reasons (per-dimension match detail). If the component has language/styling variants, they are listed with their own install commands.outcome: "shortlist" — several candidates that all fit reasonably well with no clear single winner, ranked, each with the same per-dimension reasons, plus differentiators: which specific dimension(s) actually separate them, so you can decide on that axis instead of picking arbitrarily.outcome: "no_match" — nothing in the catalog is a real fit. The closest candidates are still listed for context but explicitly marked as rejected, not returned as an answer. Do not install one of these just because it was the closest; the catalog does not have what was asked for. With resolve: "caller" this outcome is never returned, since only the server-side Resolve step reads candidates against the brief: a tie comes back as a shortlist and judging whether any candidate genuinely fits is up to you.Every result also reports briefParsedBy (hints or classifier) and resolvedBy (server or caller), and every candidate carries a summary line.
Call this before hand-rolling a component or guessing a registry name. It is deterministic: the same brief against the same catalog version always ranks candidates the same way.
Five stages. Tagging runs ahead of time and is committed as data (data/tags/); matching at query time is plain deterministic code, not a model call, so results are reproducible.
registry.json, normalize into one shape.category, domain, motion, visual_density, interaction_model, needs_external_data, decorative_only. Output is committed JSON, reviewable like code.pick_component.matchcn stores only derived tags (category, motion, density, and so on) and a link back to each registry's own install command. It never copies, stores, or redistributes any registry's component source. Every component you install still comes directly from its own registry via npx shadcn add .
| registry | homepage | components indexed |
|---|---|---|
| react-bits | reactbits.dev | 204 |
| magicui | magicui.design | 79 |
| aceternity | ui.aceternity.com | 118 |
| kokonutui | kokonutui.com | 51 |
| animate-ui | animate-ui.com | 420 |
| motion-primitives | motion-primitives.com | 33 |
| shadcn-dashboard | shadcndashboard.dev | 343 |
| assistant-ui | assistant-ui.com | 154 |
| bundui | bundui.io | 217 |
| cnippet | ui.cnippet.dev | 1128 |
| uiable | uiable.com | 969 |
| plate | platejs.org | 174 |
| react-aria | react-aria.adobe.com | 62 |
| shadcn-ui-blocks | shadcn-ui-blocks.com | 626 |
4,578 components total. The first six are the original motion/marketing family; the middle three are a product-UI expansion (forms, tables, dashboards, data display) added after checking each registry's demo/duplicate conventions individually rather than assuming they match the original six; cnippet and uiable are a second product-UI expansion, added the same way; plate and react-aria are a third, added the same way after each got its own filter fix (dropping plate's documentation pages, collapsing react-aria's tailwind/css/hooks style-prefix duplicates down to one canonical component each). shadcn-ui-blocks is a fourth: its combined free+paid index was excluded outright (82% of it paywalled, see Limitations below), but the vendor's own maintainer pointed at a separate, curated free-only index, which a real per-item check found 100% installable unauthenticated, so only that free-only index is used here. aceternity's count already excludes 163
只显示了开头部分;其余内容请在仓库中阅读