Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Descripción del creador (original en inglés)
Audit your Design System and serve your Agent the rules that keep AI-written UI on-system.
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": {
"roast-my-design-system": {
"command": "npx",
"args": [
"-y",
"roast-my-design-system",
"--mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add roast-my-design-system -- npx -y roast-my-design-system --mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"roast-my-design-system": {
"command": "npx",
"args": [
"-y",
"roast-my-design-system",
"--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": {
"roast-my-design-system": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"roast-my-design-system",
"--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 8 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub gregkozakiewicz, 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 (10.2.4) llegó al registro ayer.
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: Figma Context MCP, Claude Real Video, Figma MCP Server
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
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.
Your AI can write the UI. This makes sure it writes *your* UI.
npx roast-my-design-system@latest
Run it at the root of a UI repo. One second later, a report opens. No account. No network. No telemetry. Nothing in your repo changes.
Website, with the live example reports: www.roastds.com.
Version history is in CHANGELOG.md.
We tested this on 10 real open-source products, in 355 agent sessions, with and without this tool.
Findings each session added, counted by this tool's own rules:
| Task | Model | When | Without roast | Roast MCP and rules installed | Roast plugin with its edit hook |
|---|---|---|---|---|---|
| A new chart and a new component, 4 products, 3 runs each | Sonnet 5 | Oct 2026, roast 10.1 | 21 in 24 runs | not run | 7 in 24 runs |
| A new chart and a new component, 4 products, 3 runs each | Haiku 4.5 | Oct 2026, roast 10.1 | 72 in 24 runs | not run | 1 in 24 runs |
| Add a panel, build a dashboard, tighten a list (80 sessions) | Sonnet 5 | Sept 2026 | 7 | 9 | not run |
| A Christmas theme, 10 products | Sonnet 5 | Sept 2026 | 28 | 2 | not run |
| A new chart, 4 products, 5 runs each | Sonnet 5 | Sept 2026 | 10 in 20 runs | not run | 0 in 20 runs |
| A new chart, 4 products | Haiku 4.5 | Sept 2026 | 25 | 39 | 0 in 14 of 15 runs |
| Chart, status colour, empty state, new component | Haiku 4.5 | Sept 2026 | 42 in 16 runs | 49 in 16 runs | 3 in 51 runs |
Routine work stayed on-system with or without the tool. Work that needed something new did not.
An agent does not always call a tool when it should. In October, Sonnet called the MCP tools in 7 of 24 sessions and Haiku in 2 of 24. The edit hook runs without being asked. That is the column with the lowest numbers.
Where did the agent invent? Where the repo had nothing to copy. Dub has no chart palette. Its own charts hardcode 17 colours. Asked for a chart, Haiku hardcoded 9 more. In October, 5 of the 7 findings Sonnet left with the plugin on were chart colours on Dub. The agent kept them and wrote a comment saying the repo has no chart palette.
So the mess an agent adds is a map of the gaps in your system.
This tool draws the map.
Roast the repo to find its real design system, the mess in it, and the gaps.
Teach the agent, through generated rules and a local MCP server.
Guard every edit, so the agent does not have to remember to ask.
ROAST what is in the repo, and what is missing ↓ TEACH rules in the agent files, answers over MCP ↓ GUARD every edit checked, the PR gated
The first thing the report says: the places where the repo has no answer yet, or "No gaps found".
One gap is known for certain today, because the runs found it: charts hardcoding colours in a repo with no chart palette. 43 of 126 public repos look like that. A gap joins the list when it has been measured.
The mess the agent will copy, ranked by what fixing it is worth.
Fix, rescan, press the next button.
0 to 100. The same number every run.
Measured against three yardsticks: the ideal norms of a design system, the median of 34 product repos at the core of a 119-repo benchmark, and 10 reputable systems (Primer, Polaris, Carbon, shadcn/ui and others).
Monorepos get a score per package. packages/ui at 80 stops hiding apps/web at 40.
And 8 more kinds, all in What it measures. One HTML file. Open it, Slack it, email it.
The colour usage bar shows where the repo's colour comes from: of every 100 colour uses, how many read a theme colour by name, how many use Tailwind's palette, and how many are strays written by hand. It follows CSS variables, Tailwind themes, Sass and Less variables and JavaScript theme objects to do the counting.
The header names what the repo is built on: shadcn/ui, a Tailwind theme, MUI, Mantine, Chakra or Ant Design, and both kits when a repo uses two.
Generated from your repo, into design-system-rules.md:
canonical components the file of colour, spacing and type values known duplicates to avoid spacing steps typefaces the kit's own vocabulary
--apply writes them into every agent file you have: Claude, Cursor, GitHub Copilot, Windsurf. Every scan also checks the rules you already have for stale references.
Every number comes from a deterministic read of your files. Claude writes the explanation, labelled as written by AI and kept apart from the numbers.
Claude Code, headless, on 10 public products pinned to one commit each: cal.com, Dub, Metabase, Plausible, SigNoz, trigger.dev and four more. 259 sessions in September 2026 and 96 in October 2026 on roast 10.1, with Sonnet 5 and Haiku 4.5. The October sessions repeat the chart and new-component tasks on Plausible, SigNoz, trigger.dev and Dub at the same commits. Every changed file was judged by this tool's rules at the end of the session and at the pinned commit. A finding counts only if the session added it.
Nothing was rendered. Zero findings means the code follows these rules. It does not mean the design was reviewed. Method, tables and limits are in the research write-up, which will be published separately.
Eleven reports, hosted exactly as the tool writes them. Every number deterministic, every path real.
The full report for vercel/ai-chatbot. The verdict answers what the agent will learn here, the gap section comes first, then "What the repo teaches the agent", Claude's read of the scan:
The same report in light mode (one file, built-in toggle):
tests/, one JSON file each.tools/benchmark/.scoreHarvest(harvest) returns the score and metrics as plain data. The report and a CI check get the same numbers.The long version, with scan scoping and what the plugin runs on your machine, is in docs/reference.md.
React, Next.js, Remix, Vite Stencil, Lit, custom elements
Tailwind, sha
Solo se muestra el principio; lee el resto en el repo