Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Browse and install 75+ free animated, shadcn-compatible React components from AI Canvas.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"aicanvas": {
"command": "npx",
"args": [
"-y",
"@aicanvas/mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add aicanvas -- npx -y @aicanvas/mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"aicanvas": {
"command": "npx",
"args": [
"-y",
"@aicanvas/mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"aicanvas": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@aicanvas/mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub aicanvas-me, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.2.5) llegó al registro hace 2 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, 好縮 Short
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Smart URL shortener: create, tag and track short links on s.gooo.name.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
@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.