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)
Design engine for AI agents: images at every size, no Chrome, 2× fewer tokens
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 …”.
Descargar el archivo .mcpb del creador
El enlace lleva al archivo del propio creador; no lo alojamos ni lo reempaquetamos. Abre el archivo y Claude Desktop lo instalará.
Ejecuta esto en tu terminal
claude mcp add keyline -- docker run -i --rm ghcr.io/keyline-dev/keyline-mcp:0.8.1Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"keyline": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/keyline-dev/keyline-mcp:0.8.1"
]
}
}
}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": {
"keyline": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/keyline-dev/keyline-mcp:0.8.1"
]
}
}
}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 keyline-dev, 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 (0.8.1) llegó al registro hace 26 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas MCPB, Docker 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:★ 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.
[keyline.dev](https://keyline.dev): examples, the benchmark, and setup for every client.
Design engine for AI agents: Canva for your agent. keyline is a free MCP server for Claude Code, Claude Desktop, Cursor, Codex, Gemini CLI and any MCP client. Your agent describes a social post, ad or banner once, as a small JSON scene; keyline renders it as images and video at every size, with real text in your fonts and colors, the same every run.
No browser, and fewer tokens. No headless Chrome, Puppeteer or Playwright: one native Rust binary on Skia. Every edit replies with what's wrong at each size, so the agent fixes the design from measurements instead of screenshots: 2× fewer tokens than an agent driving headless Chrome, and 6× fewer than Playwright MCP (benchmark).
One prompt, five sizes: the layout adapts from a 4:5 post to a 728×90 leaderboard, and keyline's checks catch what doesn't fit before anything renders.
More campaigns, with motion, on keyline.dev . Every image there, and the one above, was made with keyline.
Most designs people ship today (sale posts, event flyers, ad sets) are made in tools like Canva or Adobe Express. Those tools are built for a person with a mouse, and none is a good backend for an agent:
keyline-mcp is the missing piece: an agent-first design tool, with a design format and renderer built from the ground up for a language model to author, check and export, cheaply and reproducibly. The design stays structured data (a typed layer tree with layout, tokens, styles and components), not pixels, so an agent edits it precisely instead of regenerating an image.
flowchart LR
A[Agent] -- "layer_add / layer_update" --> S[(Scene JSON)] S --> L["Layout per size scale → constraints"] L --> C["Checks defects · advisories · facts"] C -- "ok, or what to fix" --> A L --> R["Skia renderer GPU, CPU fallback"] R --> P["PNG, JPEG, WebP, PDF, animated PNG, GIF, MP4 or WebM per size"]
Start here: docs/concepts.md explains the model; docs/scene.md is the scene format and docs/tools.md the tools and configuration.
There's no GUI, and no plan for one. Every design decision is judged by one question: *how many tokens does the agent spend to get a correct image?* We measure that with a real model (Claude, through Claude Code) building a real multi-section ad.
ok or the problems, never the scene.fontWeight, borderRadius, rgba() colors), so the model writes a scene right the first time. The layout itself is keyline's own, documented, not browser-exact.role, so the agent never reads the scene to find an id.text, image (PNG, JPEG, SVG), video, icon, rect, ellipse (and arcs and rings), polygon (and stars), path (SVG path data or a named shape), line, frame (nesting, clipping, stacks, grids), spacer, firstFit, and use for componentsfill, flexGrow and priorities), grids (CSS grid: tracks, named areas, spans), hug/fill/percentage sizes with min/max and aspect ratio, direction lists and firstFit that pick what fits, constraints, placement at nine spots, a scale factor per size, per-size and per-aspect changes (media), size presets for common social and ad formats, and safe areas a platform covers , , , style names as tags); weights, italics, letter spacing, line height, case; balanced or pretty wrapping; highlights behind words; underline and strike; text on a curve; dot leaders; text filled with an image, pattern or gradient; outlines; text that knocks out its frame. Fonts work like CSS web fonts: name any Google Fonts family and the server downloads it on first use and caches it (tracked in fonts/index.json); Inter is bundled, and you can add your own font files{{brand}}, in any field or sentence) that update every field using them, components placed once or once per data row, and templates: a scene file loaded by URL or path with its variables set, rendered once per row of valuesrandom() starts, staggered children, text split into letters or words that move on their own, strokes that draw themselves, and numbers that countClaude Code (macOS or Linux): the plugin downloads keyline and checks it against the release's SHA256SUMS, or uses keyline-mcp from your PATH.
/plugin marketplace add keyline-dev/keyline
/plugin install keyline@keyline
Claude Desktop (Mac with Apple silicon, or Windows): download keyline-mcp- .mcpb from the latest release and double-click it. Designs and their renders go in ~/keyline, a folder per design, where you can also put the images and logos Claude should use. To work in folders of your own instead, open Settings → Extensions → keyline → Configure, add them, and click Save.
| Install | |
|---|---|
| macOS (Apple silicon) | brew install keyline-dev/tap/keyline-mcp |
| Linux (amd64, arm64) | sudo apt install ./keyline-mcp_ -1_amd64.deb (or _arm64), from the latest release; tarballs are there too |
| Windows (x64) | Unpack keyline-mcp-v -windows-amd64.zip and put its folder on your PATH |
| Docker | Use docker run -i --rm -v keyline:/data ghcr.io/keyline-dev/keyline-mcp as the client's command; the :stills tag leaves out ffmpeg |
| From source | cargo build --release (Rust stable; on Linux also libfontconfig1-dev libfreetype6-dev) |
Every release has a SHA256SUMS file and build attestations: gh attestation verify --repo keyline-dev/keyline. Then add keyline to your client. The command is keyline-mcp; if the client can't find it, give its full path (which keyline-mcp).
Codex (ChatGPT)
Codex is OpenAI's coding agent, included in ChatGPT plans. Its app, CLI and IDE extension share one setting:
codex mcp add keyline -- keyline-mcp
ChatGPT itself, like grok.com and the xAI API, connects only to remote servers, so it can't start keyline, which runs on your machine.
Other clients
Any client that starts local (stdio) MCP servers works, Cursor, VS Code and Gemini CLI included. Add a server named keyline whose command is keyline-mcp, in the client's MCP settings or with its mcp add command. Most clients take this JSON:
Solo se muestra el principio; lee el resto en el repo