io.github.superlcr/bilibili-huasheng-video
Script to finished Bilibili video with Huasheng: storyboard, narration, footage, export, publish.
Open source Open in the app JSON README (API)
About
Script to finished Bilibili video with Huasheng: storyboard, narration, footage, export, publish.
Details
- Kind
- MCP servers
- Topic
- No topic detected
- Publisher
- superlcr
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 0.5.0
- Stars
- 11
- Last push
- 2026-09-04T08:11:09Z
- Repository state
- ativo
- Language
- Shell
- Added
- 2026-09-04 08:01:33
- Updated
- 2026-09-07 19:01:07
- Origin id
io.github.superlcr/bilibili-huasheng-video
README
<div align="center">
# hs · Huasheng CLI
**From one sentence to a finished, publishable video**
[](https://github.com/superlcr/huasheng-cli/releases/latest)
[](https://github.com/superlcr/huasheng-cli/releases/latest)
[简体中文](README.zh.md) · **English**
</div>
---
`hs` brings [Huasheng](https://www.huasheng.cn)'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**
```bash
curl -fsSL https://raw.githubusercontent.com/superlcr/huasheng-cli/main/install.sh | sh
```
**Windows**, in PowerShell:
```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:
```bash
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.
<details>
<summary>Manual download instead of the installer</summary>
<br>
Grab the package for your platform from
[Releases](https://github.com/superlcr/huasheng-cli/releases/latest), 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:**
```bash
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".
</details>
### Sign in
Open a new terminal, sign in, and confirm that `hs` can read your credit balance:
```bash
hs auth login
hs account
```
The CLI and every AI client share `~/.hs/credentials.json`; you do not sign in separately.
## 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:
```bash
hs make --script "Three little-known facts about West Lake" --out ./out.mp4
```
Request an MG-style video:
```bash
hs make --script "Explain Song dynasty tea whisking in 30 seconds" --mode mg --out ./tea.mp4
```
Read a long script from a file:
```bash
hs make --script @script.txt --out ./video.mp4
```
`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](docs/cli.md) for parameters, step-by-step editing, resuming, and exporting. See
[Scripting and automation](docs/automation.md) 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:
```json
{
"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
```bash
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](https://developers.openai.com/codex/mcp).
#### Claude Code CLI
```bash
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
Confirming a storyboard spends credits, and publishing makes the video public. The client asks
before either action.
## More documentation
- [hs CLI guide](docs/cli.md): step-by-step creation, states, and command groups
- [Scripting and automation](docs/automation.md): JSON, exit codes, batch control, and IDs
- [Sign-in, privacy, and requirements](docs/security.md): 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. Both require your confirmation.
- Scripts and footage are uploaded to Huasheng for video creation; there is no separate telemetry
channel or background updater.
## Upgrading
```bash
hs upgrade
```
This simply re-runs the installer. `hs` performs **no** update checks and **no** silent
background updates.
## Feedback
Found a problem? Please open an
[issue](https://github.com/superlcr/huasheng-cli/issues) and include the output of
`hs --version` — it carries the commit and build time, which is the key to diagnosing anything.