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)
Turn a script into a finished video with Huasheng: storyboard, narration, footage, export.
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": {
"hs": {
"command": "npx",
"args": [
"-y",
"@superlcr/hs",
"mcp",
"serve"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add hs -- npx -y @superlcr/hs mcp servePégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"hs": {
"command": "npx",
"args": [
"-y",
"@superlcr/hs",
"mcp",
"serve"
]
}
}
}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": {
"hs": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@superlcr/hs",
"mcp",
"serve"
]
}
}
}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 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub superlcr, 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 (0.2.4) llegó al registro hace 2 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.
From one sentence to a finished, publishable video
简体中文 · English
hs brings Huasheng's video creation pipeline to the command line. Give it a sentence or a script, and it handles storyboarding, narration, footage and composition — producing a video you can export or publish directly. You can step in and adjust at any point along the way.
A single self-contained binary. No Node, no Python, no runtime to install. Every command supports --json, designed for scripts and AI clients.
Do this once, regardless of which client you use later.
Pick whichever suits you — all three give you the same binary.
macOS / Linux
curl -fsSL https://raw.githubusercontent.com/superlcr/huasheng-cli/main/install.sh | sh
Windows, in PowerShell:
irm https://raw.githubusercontent.com/superlcr/huasheng-cli/main/install.ps1 | iex
Either installer downloads the package for your platform, verifies its SHA256, and extracts it to ~/.local/bin (%LOCALAPPDATA%\Programs\hs on Windows).
With npm, if you already live in the Node ecosystem or just want to try it first:
npx @superlcr/hs --help
npm install -g @superlcr/hs # the command is still hs
The npm package is a small launcher; the binary for your platform arrives as an optional dependency, so nothing is downloaded or compiled at install time.
Manual download instead of the installer
Grab the package for your platform from Releases, extract it, and place the executable anywhere on your PATH:
| Platform | File |
|---|---|
| macOS · Apple Silicon | hs-darwin-arm64.tar.gz |
| macOS · Intel | hs-darwin-x64.tar.gz |
| Linux · x64 | hs-linux-x64.tar.gz |
| Windows · x64 | hs-windows-x64.zip |
Every release ships a SHA256SUMS file. Verifying it is recommended:
shasum -a 256 -c SHA256SUMS
Both macOS packages are signed and notarized by Apple (Developer ID Application).
The Windows package is unsigned; SmartScreen may prompt on first run — choose
"More info → Run anyway".
Open a new terminal, sign in, and confirm that hs can read your credit balance:
hs auth login
hs account
The CLI and every AI client share ~/.hs/credentials.json; you do not sign in separately.
No browser on that machine (SSH, a cloud server, a container)? Run hs auth login --no-browser, open the address it prints on any device, approve, and paste back the address the browser lands on (it starts with http://127.0.0.1 and will not load — that is expected).
Both paths use the same hs binary and the same sign-in — pick either, or both.
Use this path for exact commands, scripts, or batch jobs. hs make can start from one sentence or a complete script, run the creation workflow, wait for the finished video, and download it.
Create a video from one sentence:
hs make --script "Three little-known facts about West Lake" --out ./out.mp4
Request an MG-style video:
hs make --script "Explain Song dynasty tea whisking in 30 seconds" --mode mg --out ./tea.mp4
Read a long script from a file:
hs make --script @script.txt --out ./video.mp4
Or start from your own narration recording — a file on your computer or a public URL:
hs make --audio ./narration.m4a --out ./video.mp4
hs make --audio ./narration.m4a --transcript @words.txt --out ./video.mp4 # if you have the words
Huasheng keeps your voice and cuts footage to it. The transcript is optional; without it, Huasheng transcribes the recording. Supported formats are mp3, wav, flac, mp4 and m4a; hs uploads the file itself and you never need an internal storage address.
hs make approves the storyboard for you — that spends credits, and it prints how many. To read the storyboard and its price first, use the step-by-step commands instead. See the hs CLI guide for parameters, step-by-step editing, resuming, and exporting. See Scripting and automation for JSON, exit codes, and batches.
hs includes an MCP server. Any AI client that supports local STDIO MCP can launch it with:
{
"mcpServers": { "huasheng": { "command": "hs", "args": ["mcp", "serve"] } } }
This configuration simply tells the client to run hs mcp serve when Huasheng is needed. There is no separate hs MCP package to install, and you should not keep the command running yourself. If the client cannot find hs, replace command with the full path from which hs (where hs on Windows).
The following are setup examples for four common clients. For any other MCP client, enter the same command and args in its MCP server settings.
huasheng and choose STDIOhs; add mcp and serve as the two arguments/mcp and check that huasheng is connectedChatGPT Desktop renders interactive timeline, preview, footage, and export cards. It shares ~/.codex/config.toml with Codex CLI, so this setup also enables hs there.
hs; the default is ~/.local/bin/hsIf you changed the install location, paste the full path from which hs (where hs on Windows). Continue if the first install warns that the extension is unsigned. Claude Desktop also renders interactive cards.
codex mcp add huasheng -- hs mcp serve
codex mcp list
Do not add it again if you already configured huasheng in ChatGPT Desktop; both read ~/.codex/config.toml. See the OpenAI MCP documentation.
claude mcp add --scope user huasheng -- hs mcp serve
claude mcp list
Both commands run in the same terminal where you just signed in, so plain hs resolves; if your shell cannot find it, substitute the full path from which hs (where hs on Windows). Codex CLI and Claude Code present complete text results instead of desktop interactive cards.
After setup, say in your AI client:
Make me a 30-second video about why the sky is blue
You can inspect and refine existing projects too:
List my recent Huasheng projects
Make the narration in clip 2 shorter
Replace clip 3 with more futuristic footage
Use my own file ./b-roll.mp4 for clip 2
Change the narrator to a warmer voice, and tell me the price first
Confirming a storyboard spends credits, and publishing makes the video public. hs marks those and the other one-way tools (deleting a project, footage or a preference, joining the priority lane) as destructive, so a client that confirms destructive tools asks you first; hs itself does not prompt. Changing the voice after production and adding footage to the library spend credits too; the MCP tools quote the price when asked.
hs never receives your Bilibili password.hs does what the command says and reports the cost; whether you are asked first is up to you, your script, or your AI client.hs upgrade
For an installer build, this downloads the latest release, checks its SHA256, and swaps it in; for an npm install it runs npm i -g @superlcr/hs@latest. hs never downloads or replaces itself on its own. Once a day it asks for the latest release number and mentions it if yours is older; set HS_NO_UPDATE_CHECK=1 to turn that off.
AI clients that run hs mcp serve keep the old process until they restart. After upgrading, start a new session in Claude Code or Codex, or quit and reopen Claude Desktop; until then the client is still on the old version. Upgrading while a client is running is safe on every platform.
Found a problem? Please open an issue and include the output of hs --version — it carries the commit and build time, which is the key to diagnosing anything.