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)
Write, check and render comic panels as SVG: a deterministic compiler, no image model.
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": {
"scenet": {
"command": "uvx",
"args": [
"scenet",
"mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add scenet -- uvx scenet mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"scenet": {
"command": "uvx",
"args": [
"scenet",
"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": {
"scenet": {
"type": "stdio",
"command": "uvx",
"args": [
"scenet",
"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 creatoan, 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 (0.12.0) llegó al registro hace 8 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) 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.
A semantic DSL for comic panels, compiled to SVG.
This project is, by design, almost entirely generated by AI. It exists as a personal training ground for learning to work with AI coding tools. The architecture, code, tests and documentation are overwhelmingly AI-authored, under human direction and review.
Treat it accordingly: an experiment first, a usable tool second.
[Playground](https://creatoan.github.io/scenet/playground/) · [Gallery](https://creatoan.github.io/scenet/gallery.html) · [Documentation](https://creatoan.github.io/scenet/) · [Tutorial](https://creatoan.github.io/scenet/tutorial/first_panel.html) · [Changelog](CHANGELOG.md)
*The gallery's tour, exactly as scenet build draws it from one YAML file: no coordinates, no image model. Open it in the playground, or see every example in the gallery.*
Music has notation. A score describes the *semantics* of a piece — pitch, duration, dynamics — without describing the waveform that eventually reaches your ear. Rendering is left to an interpreter, human or machine.
Images have no such thing. SVG describes *how to draw*, not *what is depicted*: it is closer to a WAV file than to a score. Scenet is an attempt at the missing layer, narrowed to one tractable domain — the comic panel.
You write what is in the panel:
panel:
size: [1000, 1000] camera: shot: medium_shot angle: eye_level setting: place: street weather: rain cast: alice: {reference: alice, pose: pointing, at: left_third, facing: right} bob: {reference: bob, pose: arms_crossed, at: right_third, facing: left} staging:
script:
You can also write a sequence, where each panel states only what changed from the one before — borrowed from OpenUSD's sparse override, because consecutive panels in a scene share nearly all their staging:
panels:
establishing: camera: {shot: full_shot} cast: {alice: {reference: alice}, bob: {reference: bob}} reaction: over: establishing # same cast, same staging camera: {shot: close_up} # move in
Or in comic script, the format writers already use:
PANEL 1
@shot: full_shot Alice and Bob face each other on a rainy street corner.
ALICE You forgot your umbrella!
BOB (whisper) I know.
Dark Horse's published script format is read as written, and so are French scripts.
From any of these, the compiler works out the rest: how large each figure must be for a medium shot, where they stand, which way they face, how big each balloon needs to be for its text, where a balloon can sit without covering a face, and how its tail reaches the speaker's mouth — all while preserving reading order.
No generative image model is involved. This is a deterministic compiler: constraint solving and computational geometry. The same input always produces byte-identical output.
Alpha — panels, sequences and pages compile end to end, from the command line, the browser, or an editor. Framing, actor placement, balloon and caption placement, reading order, tail routing, drawn faces and the marks around them, tonal backdrops, pages of tiers and SVG emission all work, from either of two frontends — and every panel can be read by a screen reader, its description and then everything said in it, in reading order — and a page prints as a PDF with its trim, its bleed and the lettering on the black plate. Not yet built: the interpretation layer that would give a panel a *style*. See the phase plan for detail.
uv run scenet build examples/duel.panel.yaml --core --debug
uv run scenet build examples/sequence.scene.yaml --strip uv run scenet build examples/umbrella.script --strip
--core writes the resolved intermediate tier as JSON; --debug writes an overlay showing the geometry the solver was working against — silhouette hulls, face exclusion zones, anchors, gaze vectors and tail routes.
duel.panel.yaml → Panel Core (.core.json) → panel.svg
authored, resolved, fully numeric, rendered no coordinates still named & inspectable
The intermediate tier is a real, writable format rather than a hidden data structure — so layouts can be inspected, hand-adjusted, and diffed independently of how they are drawn. The approach is borrowed from Vega-Lite, which compiles a high-level grammar into a lower-level one before emitting SVG.
The [playground](https://creatoan.github.io/scenet/playground/) runs this compiler — the same Python, unmodified — in your browser under WebAssembly via Pyodide. It is not a reimplementation: the page installs the exact wheel uv build produces, so there is no second copy of the geometry to drift out of step.
Its worked examples cover every shot type, every balloon kind, every caption kind, every expression and mark, every mass kind and place, both frontends and the constraint priorities. Each one is a real file under examples/gallery/ that the test suite compiles, so the playground cannot offer an example that does not work.
The editor is Monaco, fed the *same* JSON Schema the VS Code extension uses — generated from the compiler's own models, so completion and hover documentation cannot drift from what compiles. Everything is served from one origin: no CDN, no analytics, nothing fetched from anywhere else.
The VS Code extension gives completion and inline validation for panel documents, plus a side-by-side preview. Its JSON Schema is *generated from the compiler's own models* by scenet schema, so what the editor offers is what actually compiles. A test fails if the shipped schema goes stale.
No model knows Scenet from training, so the project hands the language over instead. Driving Scenet from a model covers each kind of client:
skills/scenet, an Agent Skills folder.scenet mcp, whose tools validate, compile and render, so the model can read its own errors and fix them.pip install 'scenet[mcp]'
scenet mcp
pip install scenet
Python 3.12 or newer. No system libraries, no fonts to install, nothing to configure. Ships a py.typed marker, so mypy, pyright, ty and basedpyright read the annotations straight from the package.
from scenet import compile_source, render
result = compile_source("cast: {alice: {reference: alice}}") svg = render(result.core)
Requires uv. It manages the Python version too, so this is the whole setup:
uv sync --all-groups
uv run pytest
Checks, all of which run in CI:
uv run ruff check . && uv run ruff format --check .
uv run ty check uv run pytest
[creatoan.github.io/scenet](https://creatoan.github.io/scenet/) — or read the Markdown source under docs/, which GitHub renders without a build step.
| Tutorial | Build a panel from nothing, in fifteen minutes |
| Gallery | Every example, drawn, with its source |
| How-to guides | Sequences, comic scripts, your own characters, using it as a library |
| Language specification | Every construct, with examples |
| Shot types | Normative camera framing table |
| Panel Core | The resolved intermediate format |
| Asset contract | What a character puppet must declare |
| MCP server | The tools scenet mcp serves to a model |
| API reference | Every public name |
| Design decisions | Why it is shaped this way |
| Prior art | What already exists, and what was taken from it |
Every Python example in the documentation is executed by the test suite. An example that omits an import, or that has drifted out of step with the code, fails the build.
0BSD — see LICENSE. This is deliberately one step more permissive than MIT: you may use, copy, modify and distribute this software for any purpose, with no obligation to preserve a copyright notice or reproduce the license. No attribution is required, though it is always welcome.
Third-party components are listed in THIRD_PARTY_NOTICES.md. The lettering font arrives as an ordinary dependency under the SIL Open Font License, which does require its own notice be kept with it.
The language specification is free to implement. Anyone may build their own compiler, editor, renderer or tooling for this language, in any project, commercial or otherwise, without restriction or attribution. A notation is only worth having if it is not owned.