Aicanvas

io.github.aicanvas-me由 GitHub 帳號 aicanvas-me 發布v0.2.5更新於 Oct 24, 2026

Browse and install 75+ free animated, shadcn-compatible React components from AI Canvas.

已驗證STDIO僅桌面開發者工具媒體與設計

概覽

AI 產生的概覽

本機 MCP 伺服器,讓 AI 編輯器探索、檢視並安裝 AI Canvas 的動畫 React 元件、設計系統與範本。

可以做什麼
依分類、元件、設計系統與範本瀏覽,附數量與分頁,並可用關鍵字搜尋取得排序結果。讀取單一元件的完整中繼資料與全部原始碼,或讀取整套設計系統、範本的檔案、共用權杖與相依項目。取得任一元件的 shadcn 安裝指令,並查看單一元件的已記錄屬性。依已記錄屬性驗證檔案的 JSX,對未知、缺少或超出可選值的屬性給出行號。依一句需求產生頁面建置計畫,並取得完成頁面或元件的稽核清單。
適用情境
適合在建置 React 或 shadcn 介面時使用:讓助理尋找合適的動畫元件、在撰寫 JSX 前了解其 API、檢查用法,並在對話中完成頁面規劃或稽核。
執行需求
以 stdio 在本機執行,通常透過 npx 啟動,因此需要 Node.js 以及連線至 AI Canvas 登錄檔的網路。瀏覽中繼資料不需帳號;取得原始碼需要免費的 AI Canvas 帳號與選用的 AICANVAS_TOKEN 環境變數。AICANVAS_REGISTRY_BASE 可指向自架鏡像。
安裝前請注意
AICANVAS_TOKEN 會以 Bearer 權杖隨每次登錄檔請求送出,應視為憑證。進階設計系統與範本會回傳 HTTP 402 及升級連結,可能涉及付費內容。伺服器自身工具為唯讀,但助理可能執行安裝指令,將檔案寫入你的專案。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Aicanvas,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

@aicanvas/mcp

[Listed on mcpservers.org]

Model 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]

What it exposes

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.

ToolPurpose
list_categoriesShow every category with component counts. Orient before drilling in.
list_componentsBrowse standalone components, optionally filtered by category. Paginated.
search_componentsFuzzy keyword search across standalone AND design-system components (slugs, names, descriptions, categories, tags). Ranked results.
get_componentFull 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_commandGet the npx shadcn add @aicanvas/<slug> command for any standalone or design-system component.
list_systemsList the design systems available (e.g. Andromeda), with component and template counts.
get_systemEvery file for a whole design system, plus its shared tokens, its component install commands, and the dependency chain.
list_templatesList the ready-made templates (complete example screens), optionally filtered by design system.
get_templateEvery file for a single template (a ready-made composition), with the registry dependencies it pulls in.
get_component_propsThe documented props of one component: name, type, required, default, description. Free, no account, far smaller than the source.
validate_usageCheck 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_pageTurn 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_checklistThe 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.

Setup

Claude Desktop

Edit claude_desktop_config.json:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json
json
{  "mcpServers": {    "aicanvas": {      "command": "npx",      "args": ["-y", "@aicanvas/mcp"]    }  }}

Restart Claude Desktop. The aicanvas tools should appear in the tools list.

Cursor

Project-level (.cursor/mcp.json in your repo) or global (~/.cursor/mcp.json):

json
{  "mcpServers": {    "aicanvas": {      "command": "npx",      "args": ["-y", "@aicanvas/mcp"]    }  }}

Claude Code

Project-level .mcp.json (committed alongside your code):

json
{  "mcpServers": {    "aicanvas": {      "command": "npx",      "args": ["-y", "@aicanvas/mcp"]    }  }}

Or via the CLI:

bash
claude mcp add aicanvas -- npx -y @aicanvas/mcp

Codex

~/.codex/config.toml:

toml
[mcp_servers.aicanvas]command = "npx"args = ["-y", "@aicanvas/mcp"]

Verify it works

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:

bash
npx -y @modelcontextprotocol/inspector npx -y @aicanvas/mcp

This opens a browser UI where you can call each tool by hand.

Configuration

Env varDefaultWhat it does
AICANVAS_REGISTRY_BASEhttps://aicanvas.me/rRegistry 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.

Accounts and premium content

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.

How the registry stays fresh

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/<slug>.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.

Local development

bash
git clone https://github.com/aicanvas-me/aicanvas.gitcd aicanvas/mcpnpm installnpm run build
# Smoke-test against the deployed registry:npm run inspect
# Or point at a locally running aicanvas dev server:AICANVAS_REGISTRY_BASE=http://localhost:3000/r node dist/index.js

Edit src/index.ts, run npm run build, restart your AI editor.

License

MIT, same as the AI Canvas project.

來源:mcp/README.md,提交 870f50e

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.2.5最新Sep 16, 2026

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