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)
Transform video, audio and images, and generate media from prompts. FFmpeg, captions, models.
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.
RENDOBAR_API_KEYLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Funciona en Claude para web, escritorio y móvil:
https://api.rendobar.com/mcpAbre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"rendobar": {
"command": "npx",
"args": [
"-y",
"@rendobar/mcp"
],
"env": {
"RENDOBAR_API_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add --transport http rendobar https://api.rendobar.com/mcpclaude mcp add rendobar --env RENDOBAR_API_KEY=your-value -- npx -y @rendobar/mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"rendobar": {
"url": "https://api.rendobar.com/mcp"
}
}
}Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"rendobar": {
"command": "npx",
"args": [
"-y",
"@rendobar/mcp"
],
"env": {
"RENDOBAR_API_KEY": "your-value"
}
}
}
}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": {
"rendobar": {
"type": "http",
"url": "https://api.rendobar.com/mcp"
}
}
}Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"rendobar": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@rendobar/mcp"
],
"env": {
"RENDOBAR_API_KEY": "your-value"
}
}
}
}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.
ChatGPT solo se conecta a servidores en internet:
https://api.rendobar.com/mcpLos nombres de los menús pueden variar un poco según el plan y con el tiempo.
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.
Todavía no hemos leído la lista de herramientas de este servidor; revisamos los endpoints por turnos.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con el dominio rendobar.com (el registro comprueba quién es dueño del dominio)
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Aún sin revisar; revisamos los endpoints por turnos
Aún sin revisar; revisamos los endpoints por turnos
Aún sin revisar; leemos la lista de herramientas cuando revisamos el endpoint
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.
Debes completar: RENDOBAR_API_KEY
Funciona de las dos formas: instálalo en tu computadora o conéctate a la versión en la nube.
El repo de GitHub cambió por última vez –, y la última versión (1.13.0) llegó al registro hace 27 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.
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.
@rendobar/mcp
Serverless media processing for AI agents.
The official Model Context Protocol server for Rendobar.
Docs · npm · Glama · Discord
@rendobar/mcp is the official Model Context Protocol server for Rendobar, a serverless media processing API. The server runs locally over stdio and reads files straight from your disk, so an AI agent can take a file off your machine, process it on Rendobar's infrastructure, and hand back a hosted URL.
Rendobar covers both sides of media work.
Transform what you have. Run any FFmpeg command against video, audio or images the way you would write it locally. Inspect a file and get a normalized summary plus the full ffprobe report. Compose video from a declarative JSON timeline. Compress to a target size or quality, where the encoder searches candidate encodes and returns the smallest file that clears the bar. Burn in subtitles from SRT, VTT or ASS, or let it transcribe when none is given.
Generate what you do not. Create an image from a text prompt on hosted open-weight diffusion models. Edit up to four reference images from a written instruction, no masks and no coordinates. Upscale on a one-step diffusion restoration model that reconstructs detail rather than only sharpening. The same model-backed layer drives the transcription and keyword highlighting behind animated captions, so this is not an image-only capability.
The job list grows over time, so this README names families rather than types. list_job_types reads the current set live from the registry on every call.
Published to npm as @rendobar/mcp and to the official MCP Registry as com.rendobar/mcp.
You: Mute the first 3 seconds of
intro.mp4.
The agent tells you to install FFmpeg. Then you go looking for how to gate a filter on a timestamp, land on volume=enable='lt(t,3)', and lose another few minutes to quote escaping in your shell. Nobody remembers that syntax, which is the problem.
You: Mute the first 3 seconds of
intro.mp4.
upload_file { "path": "~/clips/intro.mp4" }
// → { "downloadUrl": "https://cdn.rendobar.com/u/abc123/intro.mp4", "sizeBytes": 4821004 }
submit_job { "type": "ffmpeg", "inputs": { "intro.mp4": "https://cdn.rendobar.com/u/abc123/intro.mp4" }, "params": { "command": "-i intro.mp4 -af \"volume=enable='lt(t,3)':volume=0\" -c:v copy out.mp4" } } // → { "jobId": "job_9f2a", "status": "waiting" }
get_job { "jobId": "job_9f2a", "wait": true } // → complete · $0.01 · https://cdn.rendobar.com/o/job_9f2a/out.mp4
The agent writes the filter. Rendobar runs it. Nothing gets installed on your machine, and -c:v copy means the video stream is never re-encoded.
Hit a size budget.
You: Get
demo.movunder 25 MB so I can email it.
upload_file { "path": "~/recordings/demo.mov" }
// → { "downloadUrl": "https://cdn.rendobar.com/u/7c1e/demo.mov", "sizeBytes": 251658240 }
submit_job { "type": "compress.target", "inputs": { "source": "https://cdn.rendobar.com/u/7c1e/demo.mov" }, "params": { "for": "web", "target": { "maxSize": "25MB" } } } // → { "jobId": "job_4b8d", "status": "waiting" }
get_job { "jobId": "job_4b8d", "wait": true } // → complete · https://cdn.rendobar.com/o/job_4b8d/out.mp4 · 23.8 MB
You give it the ceiling, not a bitrate. The encoder searches candidate encodes and returns the smallest file that still clears the quality bar, so you are not guessing at CRF values to land under a mail server's limit.
Generate an image.
You: Make a 1920x1080 title card for a video about deep sea diving.
submit_job { "type": "image.generate",
"inputs": {}, "params": { "model": "standard", "prompt": "Title card for a deep sea diving documentary. Shafts of light through deep blue water, small diver silhouette, empty space across the upper third for a title.", "width": 1920, "height": 1080 } } // → { "jobId": "job_2fa7", "status": "waiting" }
get_job { "jobId": "job_2fa7", "wait": true } // → complete · https://cdn.rendobar.com/o/job_2fa7/out.png
inputs is empty because nothing is being transformed. Ask for a tier (economy, standard, premium) and the platform picks the model, or pin an exact model id to reach its own controls. Requested dimensions are snapped to what the chosen model can actually render.
Six more tools, and the prompts that reach them.
You: What can Rendobar actually do?
list_job_types {}
// → { "jobTypes": [ { "type": "compose", "tag": "Compose", // "summary": "Render a video from a declarative JSON timeline", // "acceptsMedia": ["video", "image", "audio"] }, ... ], // "guidance": "..." }
Read live from the job registry on every call, which is why nothing in this README enumerates job types. A new one appears here without a release.
You: How much credit is left?
get_account {}
// → { "balance": "$4.86", "balanceUsd": 4.86, "plan": "free", "isPro": false, // "limits": { "concurrentJobs": 1, "maxFileSize": "500 MB", "jobTimeoutMin": 60 } }
Worth a call before submitting something expensive.
You: What did I run this morning?
list_jobs { "status": "complete", "limit": 5 }
// → { "jobs": [ { "id": "job_9f2a", "type": "ffmpeg", "status": "complete", // "createdAt": "2026-08-04T09:12:00Z", "cost": "$0.01", // "output": { "url": "https://cdn.rendobar.com/o/job_9f2a/out.mp4" } } ] }
The compact row is enough to find a result you lost. Call get_job when you need the full output.
You: Stop that one, I picked the wrong file.
cancel_job { "jobId": "job_9f2a" }
// → { "id": "job_9f2a", "status": "cancelled" }
Works on waiting, dispatched and running jobs. A running job's upstream execution is stopped too, so you are not billed for work you cancelled.
You: Where can this land once it's done?
list_storage {}
// → { "storage": [ { "id": "prod-media", "provider": "s3", "bucket": "acme-prod-media", // "access": "deliver", "defaultDestination": true, "pending": false } ], // "note": "..." }
The buckets connected on the Storage page, without the endpoint or region an agent has no use for. Use the id in destinations, or as storage:// / in any input.
You: What's already in the archive bucket?
list_storage_files { "storageId": "raw-archive" }
// → { "folders": [ { "prefix": "2026/", "uri": "storage://raw-archive/2026/" } ], // "files": [ { "key": "notes.txt", "size": 800, "lastModified": "2026-09-01T00:00:00.000Z", // "uri": "storage://raw-archive/notes.txt" } ], // "cursor": null }
Every entry carries its own storage:// uri, ready to hand straight to submit_job. Pass a folder's prefix to go one level deeper.
Rendobar has two MCP servers. Pick by whether the agent needs your filesystem.
@rendobar/mcp (this package) | Hosted (api.rendobar.com/mcp) | |
|---|---|---|
| Transport | stdio, spawned by your client | Streamable HTTP |
| Reads local files | Yes. That is the reason it exists | No. The server has no disk |
| Auth | API key | OAuth in the browser, or a Bearer key |
| Best for | Claude Desktop, Cursor, Cline, Zed | claude.ai, ChatGPT, hosted gateways |
Hosted, no API key, one command:
claude mcp add --transport http rendobar https://api.rendobar.com/mcp
Local, for filesystem access. Get a key at app.rendobar.com → Settings → API Keys, then:
claude mcp add rendobar -s user --env RENDOBAR_API_KEY=rb_... -- npx -y @rendobar/mcp
Already ran rb login with the Rendobar CLI? Drop --env. The server finds the credentials file.
Claude Desktop, Cursor, Cline, Windsurf
Same block for all four. Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows). Cursor: ~/.cursor/mcp.json on every OS. Windsurf: ~/.codeium/windsurf/mcp_config.json on every OS. Cline: MCP panel → Configure.
On Linux, use Cursor, Windsurf, Cline, Zed, VS Code or Continue. Claude Desktop has no Linux build, so it is the one client on this list you cannot use there. The server itself runs fine on Linux.
{
"mcpServers": { "rendobar": { "command": "npx", "args": ["-y", "@rendobar/mcp"], "env": { "RENDOBAR_API_KEY": "rb_..." } } } }
Restart the client afterwards.
Zed, VS Code, Continue
Zed uses context_servers instead of mcpServers, in ~/.config/zed/settings.json:
{
"context_servers": { "rendobar": { "source": "custom", "command": "npx", "args": ["-y", "@rendobar/mcp"], "env": { "RENDOBAR_API_KEY": "rb_..." } } } }
VS Code 1.101+, in .vscode/mcp.json, prompts for the key instead of storing it:
{
"servers": { "rendobar": { "command": "npx", "args": ["-y", "@rendobar/mcp"], "env": { "RENDOBAR_API_KEY": "${input:rendobarKey}" } } }, "inputs": [{ "id": "rendobarKey", "type": "promptString", "password": true, "description": "Rendobar API Key" }] }
Continue, in .continue/mcpServers/rendobar.yaml:
type: stdio
command: npx args: ["-y", "@rendobar/mcp"] env: RENDOBAR_API_KEY: rb_...
</details>
Runs on macOS, Linux and Windows. Every release is tested on all three in CI. There are no native dependencies, so architecture does not matter: x64 and arm64 both work. Needs Node 20.10 or later, and the server checks at startup and exits with a clear message on older versions.
| Tool | Purpose |
|---|---|
upload_file | Upload a local file. Returns a URL to use in submit_job. |
list_job_types | Every active job type, read live. Call this first. |
submit_job | Submit a job of any type. |
get_job | Status and result. Pass wait: true to long-poll for ~50s. |
list_jobs | Recent jobs. |
cancel_job | Cancel a waiting, dispatched or running job. |
get_account | Balance, plan limits, active job count. |
list_storage | Buckets connected on the Storage page, for storage:// inputs and destinations. |
list_storage_files | Folders and files in a connected bucket, each with its storage:// URI. |
**`ffmp
Solo se muestra el principio; lee el resto en el repo