原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Hs

作者:superlcr版本 0.2.4i★ –i在你的电脑上运行
注册名称io.github.superlcr/hs

安装

概览

作者提供的说明(英文原文)

Turn a script into a finished video with Huasheng: storyboard, narration, footage, export.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 设计、图片与音频

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "hs": {
      "command": "npx",
      "args": [
        "-y",
        "@superlcr/hs",
        "mcp",
        "serve"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add hs -- npx -y @superlcr/hs mcp serve

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "hs": {
      "command": "npx",
      "args": [
        "-y",
        "@superlcr/hs",
        "mcp",
        "serve"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "hs": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@superlcr/hs",
        "mcp",
        "serve"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 superlcr 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“设计、图片与音频”中的其他服务器比较i

  • 星标数多于此分类中其他 2186 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2186 个服务器的 28% 更新
  • 基础检查结果等于或优于此分类中其他 2186 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Hs 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.4)于2个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Figma Context MCP

作者:GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

在你的电脑上运行★ 16,165MIT5个月前更新
安装

Claude Real Video

作者:HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

在你的电脑上运行★ 2,284MIT2个月前更新
安装

Figma MCP Server

作者:figma

The Figma MCP server brings Figma design context directly into your AI workflow.

在云端运行★ 2,15213个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

hs · Huasheng CLI

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.

Step 1: install and sign in

Do this once, regardless of which client you use later.

Install

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:

PlatformFile
macOS · Apple Siliconhs-darwin-arm64.tar.gz
macOS · Intelhs-darwin-x64.tar.gz
Linux · x64hs-linux-x64.tar.gz
Windows · x64hs-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".

Sign in

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).

Step 2: choose how you use it

Both paths use the same hs binary and the same sign-in — pick either, or both.

Option 1: use hs CLI directly

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.

Option 2: use hs through MCP in an AI client

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.

ChatGPT Desktop App
  1. Open Settings → MCP servers → Add server
  2. Enter huasheng and choose STDIO
  3. Set Command to the full path to hs; add mcp and serve as the two arguments
  4. Save and restart, then type /mcp and check that huasheng is connected

ChatGPT Desktop renders interactive timeline, preview, footage, and export cards. It shares ~/.codex/config.toml with Codex CLI, so this setup also enables hs there.

Claude Desktop App
  1. Download [huasheng.mcpb](https://github.com/superlcr/huasheng-cli/releases/latest/download/huasheng.mcpb)
  2. Double-click it, then select Install in Claude Desktop
  3. Confirm the path to hs; the default is ~/.local/bin/hs

If 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 CLI
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 Code CLI
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.

Use it through conversation

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.

More documentation

  • hs CLI guide: step-by-step creation, states, and command groups
  • Scripting and automation: JSON, exit codes, batch control, and IDs
  • Sign-in, privacy, and requirements: credentials, network boundaries, platforms

Safety boundaries

  • The CLI and every AI client share one local credential; hs never receives your Bilibili password.
  • Approving a storyboard spends credits, and publishing goes public. So do changing the voice after production and adding footage to the library, and those credits are not refunded. 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.
  • Scripts, narration recordings, and footage are uploaded to Huasheng for video creation; there is no separate telemetry channel or background updater. The only other connection is a once-a-day check of the latest release number on GitHub, which sends nothing but the hs version and can be turned off.

Upgrading

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.

Feedback

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.

问 PopNx