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PopNx MCPMCP servers for people who use AI · explained in plain words

Matchcn

by francesco0242version 0.2.2i★ –iRuns on your computer
Registry nameio.github.francesco0242/matchcn

Install

Overview

Description from the maker (original English)

Semantic index across shadcn-format component registries: find components by what they do.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "matchcn": {
      "command": "npx",
      "args": [
        "-y",
        "matchcn"
      ]
    }
  }
}

Run this in your terminal

claude mcp add matchcn -- npx -y matchcn

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "matchcn": {
      "command": "npx",
      "args": [
        "-y",
        "matchcn"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "matchcn": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "matchcn"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account francesco0242, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 18659 servers in this category
  • Published to the registry more recently than 50% of the other 18659 servers in this category
  • Basic checks equal to or better than 100% of the other 18659 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Matchcn safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.2) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, alalanet — check before you pay

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

by formulahendryEarly↓ 66/wk★ 440Updated 14 months ago

Runs on your computer

Remote Desktop Commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

by desktop-commanderGrowing★ 211Updated 3 days ago

Runs in the cloud✓ desktopcommander.app

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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


The problem

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.

Quick start

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_component to find UI components that

match my brief. Show me the match reasons and install command before

adding a component.

Example

$ 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.

For AI agents

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.

How it works

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.

  1. Ingest — fetch each registry's registry.json, normalize into one shape.
  2. Tag — one batched call per chunk of components to classifier.dev, across seven dimensions: category, domain, motion, visual_density, interaction_model, needs_external_data, decorative_only. Output is committed JSON, reviewable like code.
  3. Match — parse the brief into the same seven dimensions with one classifier.dev call, then rank every tagged component against it in plain code. Each dimension's contribution to the ranking is weighted by its own confidence, so a weak tag pulls its weight down instead of polluting the result.
  4. Resolve — for close calls, one more call reviews the top candidates' real descriptions and picks a winner, or says none of them fit. Skipped when the top match is already clearly ahead, to save a round trip.
  5. Surface — the MCP server in this repo. One tool, pick_component.

Registries indexed

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 .

registryhomepagecomponents indexed
react-bitsreactbits.dev204
magicuimagicui.design79
aceternityui.aceternity.com118
kokonutuikokonutui.com51
animate-uianimate-ui.com420
motion-primitivesmotion-primitives.com33
shadcn-dashboardshadcndashboard.dev343
assistant-uiassistant-ui.com154
bunduibundui.io217
cnippetui.cnippet.dev1128
uiableuiable.com969
plateplatejs.org174
react-ariareact-aria.adobe.com62
shadcn-ui-blocksshadcn-ui-blocks.com626

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

Only the beginning is shown; read the rest in the repo

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