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)
Browse and install 75+ free animated, shadcn-compatible React components from AI Canvas.
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": {
"aicanvas": {
"command": "npx",
"args": [
"-y",
"@aicanvas/mcp"
]
}
}
}在终端中运行这条命令
claude mcp add aicanvas -- npx -y @aicanvas/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"aicanvas": {
"command": "npx",
"args": [
"-y",
"@aicanvas/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": {
"aicanvas": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@aicanvas/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8日
注册名称已通过 GitHub 账户 aicanvas-me 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(0.2.5)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, Brontide agent arena
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.
THE MECH ARENA BUILT FOR AI AGENTS. HUMANS WELCOME. Pilot mech duels over MCP, free, no sign-in.
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。
@aicanvas/mcpModel Context Protocol server for AI Canvas. Lets your AI editor (Claude Code, Cursor, Claude Desktop, Codex) discover and install AI Canvas components without leaving the chat.
You: "find me an animated card stack"
AI: [calls search_components → ranks matches → picks polaroid-stack] [calls get_install_command → returns: npx shadcn add @aicanvas/polaroid-stack] [runs the command — file lands in your project] You: "make the rotation more dramatic" AI: [edits the file directly]
Thirteen tools, derived from the live aicanvas.me registry. Adding a component to the website auto-updates the MCP within minutes. The registry holds 80+ standalone components, plus the Andromeda design system with its own components and templates.
| Tool | Purpose |
|---|---|
list_categories | Show every category with component counts. Orient before drilling in. |
list_components | Browse standalone components, optionally filtered by category. Paginated. |
search_components | Fuzzy keyword search across standalone AND design-system components (slugs, names, descriptions, categories, tags). Ranked results. |
get_component | Full metadata plus complete .tsx source code for one component. Resolves both standalone slugs and design-system component slugs (e.g. andromeda-heat-grid). |
get_install_command | Get the npx shadcn add @aicanvas/ command for any standalone or design-system component. |
list_systems | List the design systems available (e.g. Andromeda), with component and template counts. |
get_system | Every file for a whole design system, plus its shared tokens, its component install commands, and the dependency chain. |
list_templates | List the ready-made templates (complete example screens), optionally filtered by design system. |
get_template | Every file for a single template (a ready-made composition), with the registry dependencies it pulls in. |
get_component_props | The documented props of one component: name, type, required, default, description. Free, no account, far smaller than the source. |
validate_usage | Check a file's JSX against the documented props of the AI Canvas components it imports: unknown props, missing required props, values outside a prop's options, each with a line number. |
compose_page | Turn a one-line brief into a build plan: closest template, one component per part with alternatives, install order (tokens first), and the parts nothing covers. Plans only, generates no code. |
get_audit_checklist | The checklist to run on a finished page or component: install completeness, props, both themes, 320px layout, motion cleanup, keyboard and contrast, composition. |
All tools are read-only. Nothing is mutated on AI Canvas's side.
The workflow the last four tools are built for: compose_page to plan, get_component_props to read each API before writing JSX, validate_usage on the finished file, get_audit_checklist before calling it done.
Standalone components and design-system components are kept in separate buckets. list_components and list_categories cover the 80+ standalones only, so the catalog stays clean. Design-system components are reached through list_systems / get_system, and are also resolvable by slug through get_component, get_install_command, and search_components.
Edit claude_desktop_config.json:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.config/Claude/claude_desktop_config.json{
"mcpServers": { "aicanvas": { "command": "npx", "args": ["-y", "@aicanvas/mcp"] } } }
Restart Claude Desktop. The aicanvas tools should appear in the tools list.
Project-level (.cursor/mcp.json in your repo) or global (~/.cursor/mcp.json):
{
"mcpServers": { "aicanvas": { "command": "npx", "args": ["-y", "@aicanvas/mcp"] } } }
Project-level .mcp.json (committed alongside your code):
{
"mcpServers": { "aicanvas": { "command": "npx", "args": ["-y", "@aicanvas/mcp"] } } }
Or via the CLI:
claude mcp add aicanvas -- npx -y @aicanvas/mcp
~/.codex/config.toml:
[mcp_servers.aicanvas]
command = "npx" args = ["-y", "@aicanvas/mcp"]
Inside any of the AI editors above, ask:
"What categories of components does AI Canvas have?"
You should see all 11 categories with counts. If you don't, check the host's MCP logs. Typically a "Failed to spawn process" or network error means npx couldn't fetch the package, or the host wasn't restarted after editing the config.
To inspect the server outside an editor:
npx -y @modelcontextprotocol/inspector npx -y @aicanvas/mcp
This opens a browser UI where you can call each tool by hand.
| Env var | Default | What it does |
|---|---|---|
AICANVAS_REGISTRY_BASE | https://aicanvas.me/r | Registry root URL. Override only for local development against a self-hosted mirror. |
AICANVAS_TOKEN | _(none)_ | Optional per-account token. The website bakes it into the MCP config it gives you. It identifies your AI Canvas account so source pulls are authorized and any premium content you own unlocks. Sent as a Bearer token on every registry request. Without it you are anonymous: metadata browsing still works, but pulling a component's source returns a short "create a free account" notice instead of the code. |
Browsing metadata (list_categories, list_components, search_components, list_systems, list_templates, get_install_command) is free and needs no account. Pulling actual source (get_component, get_system, get_template) runs against a free AI Canvas account: set AICANVAS_TOKEN from your account and the website gives you the ready-made config. Without a token, a free-component source pull returns a short "create a free account" notice instead of the code, and premium content (full design systems and templates) returns HTTP 402 with an upgrade link at aicanvas.me/pricing. Update anytime with npx @aicanvas/mcp@latest.
The MCP fetches https://aicanvas.me/r/aicanvas-mcp.json on first use and caches it for 5 minutes. New components on AI Canvas appear in the MCP automatically, no package update required.
The full source code for each component is fetched on demand from /r/ .json (the same shadcn registry items the CLI installs).
The prop tables come from https://aicanvas.me/r/aicanvas-props.json, parsed at build time from each component's own JSDoc, so they cannot drift from the source. Same 5-minute cache.
git clone https://github.com/aicanvas-me/aicanvas.git
cd aicanvas/mcp npm install npm run build
npm run inspect
AICANVAS_REGISTRY_BASE=http://localhost:3000/r node dist/index.js
Edit src/index.ts, run npm run build, restart your AI editor.
MIT, same as the AI Canvas project.