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)
AI video dubbing via OrcaRouter (model orca/dub): upload a video or URL, poll, download the MP4.
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.
ORCADUB_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 …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"orcadub": {
"command": "npx",
"args": [
"-y",
"@orcadub/cli"
],
"env": {
"ORCADUB_API_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add orcadub --env ORCADUB_API_KEY=your-value -- npx -y @orcadub/cliCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"orcadub": {
"command": "npx",
"args": [
"-y",
"@orcadub/cli"
],
"env": {
"ORCADUB_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": {
"orcadub": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@orcadub/cli"
],
"env": {
"ORCADUB_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.
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 Continuum-AI-Corp, 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.
Debes completar: ORCADUB_API_KEY
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 (1.4.0) llegó al registro hace 4 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: 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.
The official [MCP](https://modelcontextprotocol.io) server for [OrcaDub](https://orcadub.orcarouter.ai) — AI video dubbing, driven from your agent.
Website · API Docs · Get an API key · Config examples · Releases
Give any MCP-capable agent — Claude Code, Claude Desktop, Codex CLI, Cursor, Windsurf — the ability to dub a video into another language: upload a file or pass a URL, submit a job to the orca/dub model through the OrcaRouter gateway, poll progress, and download the finished MP4.
Every operation is a one-shot subcommand (no resident server needed):
export ORCADUB_API_KEY=sk-orca-... # from https://www.orcarouter.ai/console
npx -y @orcadub/cli health npx -y @orcadub/cli upload --path ./clip.mp4 npx -y @orcadub/cli create --source-lang en --target-lang ja \ --url https://youtu.be/... --opt preserve_bgm=true npx -y @orcadub/cli get --video-id npx -y @orcadub/cli download --video-id --dest ./out.mp4
Optional create parameters use repeatable --opt key=val (e.g. --opt watermark=false --opt resolution=1080p --opt glossary.OrcaDub=OrcaDub). Results print as JSON on stdout; errors go to stderr with a non-zero exit.
With no subcommand the same binary runs as an MCP stdio server (npx -y @orcadub/cli).
The dub-video Skill teaches an agent when to dub, which billed parameters it must confirm, and how to run the upload → create → poll → download workflow. Install it interactively:
npx -y @orcadub/cli skill install
The guided installer opens with a balanced 8-row ORCADUB wordmark, then lets you:
Space to toggle, / to filter, a to select all, n to clear all, and Enter to confirm.It supports 36 platforms: the 33-platform Comet-compatible catalog plus Hermes, OpenClaw, and Command Code. Use --lang zh or --lang en to skip the language screen. For unattended or agent-driven setup, select targets explicitly:
# Current project
npx -y @orcadub/cli skill install \ --platform claude --platform codex --scope project --lang en --yes
npx -y @orcadub/cli skill install \ --platform codex --scope global --lang zh --yes
Use --yes to accept detected platforms (or all platforms when none are detected) without opening the installer. Use --json for decoration-free structured output. Set NO_COLOR (or use TERM=dumb) for a color-free installer. Existing identical content is left unchanged; an existing different Skill is preserved unless --force is provided. Skill installation needs network access to the canonical orcadub-plugin repository, but it does not require ORCADUB_API_KEY and does not contact OrcaRouter.
claude mcp add orcadub -e ORCADUB_API_KEY=sk-orca-... -- npx -y @orcadub/cli
Then just ask your agent: *"Dub this into Chinese: https://www.youtube.com/watch?v=…"*
An OrcaRouter API key is required — every tool call is authenticated:
sk-orca-...).ORCADUB_API_KEY environment variable (see below).Dubbing jobs are billed per minute of source video. Without a key the server still starts, but every tool call returns a sign-up redirect to the console.
claude mcp add orcadub -e ORCADUB_API_KEY=sk-orca-... -- npx -y @orcadub/cli
Add to claude_desktop_config.json:
{
"mcpServers": { "orcadub": { "command": "npx", "args": ["-y", "@orcadub/cli"], "env": { "ORCADUB_API_KEY": "sk-orca-..." } } } }
codex mcp add orcadub --env ORCADUB_API_KEY=sk-orca-... -- npx -y @orcadub/cli
Any host that launches stdio MCP servers works with the same shape: command npx, args ["-y", "@orcadub/cli"], env ORCADUB_API_KEY. Ready-to-copy configuration files for Claude Code, Codex, Cursor and Windsurf live in examples/.
Images are published to GHCR for linux/amd64 and linux/arm64:
docker pull ghcr.io/continuum-ai-corp/orcadub-mcp-server:latest
claude mcp add orcadub -e ORCADUB_API_KEY=sk-orca-... -- \ docker run --rm -i -e ORCADUB_API_KEY -v "$PWD:$PWD" -w "$PWD" \ ghcr.io/continuum-ai-corp/orcadub-mcp-server:latest
Or as host JSON config:
{
"mcpServers": { "orcadub": { "command": "docker", "args": ["run", "--rm", "-i", "-e", "ORCADUB_API_KEY", "-v", "/path/to/videos:/work", "-w", "/work", "ghcr.io/continuum-ai-corp/orcadub-mcp-server:latest"], "env": { "ORCADUB_API_KEY": "sk-orca-..." } } } }
Note: dub_upload and dub_download read/write local paths, so mount the directory you upload from / download to (the -v flag) — paths you pass to the tools must be valid inside the container.
Download the binary for your platform from the releases page (verify with checksums.txt), then register it directly:
# example: Linux amd64 via gh CLI
gh release download v0.1.0 -R Continuum-AI-Corp/orcadub-mcp-server \ -p 'orcadub-mcp-server_*_linux_amd64' -O ~/bin/orcadub-mcp-server && chmod +x ~/bin/orcadub-mcp-server claude mcp add orcadub -e ORCADUB_API_KEY=sk-orca-... -- ~/bin/orcadub-mcp-server
git clone https://github.com/Continuum-AI-Corp/orcadub-mcp-server && cd orcadub-mcp-server && make build
| Environment variable | Required | Description |
|---|---|---|
ORCADUB_API_KEY | yes | OrcaRouter sk-orca-... key, sent as Authorization: Bearer on every request. The gateway resolves your workspace and billing from it. |
The gateway address (https://api.orcarouter.ai) is fixed in the binary — there is nothing else to configure.
| Tool | Description | |
|---|---|---|
dub_health | End-to-end probe of gateway → orca/dub routing. No job is created, nothing is billed. | |
dub_upload | Upload a local video file; returns the file_id for dub_create. Files above 64 MiB are chunked automatically (up to 8 GiB). | |
dub_create | Submit a dubbing job (billed). Source is exactly one of file_id or url (YouTube and direct links are fetched server-side). Required: source_lang, target_lang (never auto), and video_name when using file_id. Optional knobs cover content profiles, glossaries, translation style, background-music preservation, lipsync, watermarking, resolution/ratio and more. | |
dub_get | Poll a job: `queued → in_progress → completed \ | failed with integer progress. On completion the response includes content_url (Bearer-authenticated delivery address, never expires) and job_id`. |
dub_download | Save a completed job's MP4 to a local path (refuses to overwrite existing files). |
Supported languages: en zh ja ko fr de es pt ru ar it hi tr th vi id bn pl nl uk fil el cs sv da no fi sk.
A typical agent conversation:
User: Dub this into Chinese: https://www.youtube.com/watch?v=xxxx
Agent: *(dub_create with source_lang=en, target_lang=zh, url=…)* → job queued → *(polls dub_get every ~30 s)* → completed → *(asks: download locally? default: current directory)* → *(dub_download)* → "Saved to ./My-Video-zh.mp4 — re-download any time:
curl -H "Authorization: Bearer sk-orca-..." -o out.mp4"
Direct tool usage from an agent prompt works too — for example dub_create {"source_lang":"en","target_lang":"zh","url":"https://…","glossary":{"OrcaRT":"OrcaDub Realtime"}}.
| Symptom | Cause / fix |
|---|---|
Tool calls return not authorized … www.orcarouter.ai/console | ORCADUB_API_KEY is unset — register, export the key, restart the session. |
401 | Invalid or expired key — re-issue on the OrcaRouter console. |
402 insufficient_credit | Top up your OrcaRouter balance (per-minute billing). |
429 free_quota_exceeded | Free-tier limit reached. |
task_not_exist on dub_get | The id wasn't created through this gateway — use the id exactly as returned by dub_create. |
go build ./...
go test ./... -count=1
Layout: cmd/ (entrypoint) · internal/ (HTTP client, Skill installer, tool layer, wire types) · npm/ (npx launcher that downloads the platform binary from GitHub Releases) · server.json (MCP Registry manifest).
git tag v0.1.0 && git push origin v0.1.0.npm-publish job stamps the tag version into npm/package.json and publishes @orcadub/cli to npm (requires the NPM_TOKEN repo secret).server.json and publishes it to the MCP Registry.MIT