Shotflow MCP

Name: Shotflow MCP
Author: JOHNZhang-ui

by JOHNZhang-uiversion 1.0.0i★ –iRuns on your computer

Registry nameio.github.JOHNZhang-ui/shotflow-mcp

Install

Overview

Description from the maker (original English)

ShotFlow MCP Server — AI分镜脚本与视频生成智能体，支持生成专业分镜、视频、镜头重生成、配额查询等能力。

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiVery new↓ 31/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: Streamable HTTP
Category: Other
You need to fill in: MCP_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: SHOTFLOW_API_URL, MCP_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "shotflow": {
      "command": "npx",
      "args": [
        "-y",
        "shotflow-mcp-server"
      ],
      "env": {
        "SHOTFLOW_API_URL": "your-value",
        "MCP_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add shotflow --env SHOTFLOW_API_URL=your-value --env MCP_API_KEY=your-value -- npx -y shotflow-mcp-server

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "shotflow": {
      "command": "npx",
      "args": [
        "-y",
        "shotflow-mcp-server"
      ],
      "env": {
        "SHOTFLOW_API_URL": "your-value",
        "MCP_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "shotflow": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "shotflow-mcp-server"
      ],
      "env": {
        "SHOTFLOW_API_URL": "your-value",
        "MCP_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

SHOTFLOW_API_URL env
ShotFlow Express API 地址（URL 格式，例如 http://localhost:3003）
MCP_API_KEY secret env
MCP Server 认证 Key（可选）

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account JOHNZhang-ui, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 18595 servers in this category
Published to the registry more recently than 13% of the other 18595 servers in this category
Basic checks equal to or better than 100% of the other 18595 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Shotflow MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: MCP_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Aiterm MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Aiterm MCP

Persistent terminals and one launcher for Claude, Codex, Grok, Cursor, and Antigravity harnesses.

by kiteponGrowing↓ 4.2K/wkUpdated today

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

ShotFlow MCP Server

让 AI Agent 直接调用专业分镜脚本生成能力

ShotFlow MCP Server 是 ShotFlow 的 Model Context Protocol 接口实现，让任何支持 MCP 的 AI 客户端（Claude Desktop、Cursor、Cline、VS Code Copilot 等）都能直接调用专业分镜脚本与视频生成能力。

在线使用

无需安装，直接配置 URL 即可使用：

https://aishotflow.cn/mcp

功能一览

Tool	说明
`generate_storyboard`	从剧本/创意描述生成专业分镜脚本（6种创作类型 × 7种视觉风格）
`generate_video`	从分镜镜头生成视频（Pro 功能）
`check_video_status`	查询视频生成状态
`regenerate_shot`	单镜头重新生成
`list_video_tasks`	列出视频任务历史
`check_quota`	查询今日配额
`check_health`	检查服务健康状态

Resource	说明
`shotflow://templates/creative-types`	6种创作类型模板与默认参数
`shotflow://templates/visual-styles`	7种视觉风格参考与关键词

快速接入

Claude Desktop

编辑配置文件（macOS: ~/Library/Application Support/Claude/claude_desktop_config.json，Windows: %APPDATA%\Claude\claude_desktop_config.json）：

"mcpServers": { "shotflow": { "url": "https://aishotflow.cn/mcp" } } }

重启 Claude Desktop，点击「Attached tools」确认 shotflow 已加载。

Cursor IDE

在项目根目录创建 .cursor/mcp.json：

"mcpServers": { "shotflow": { "url": "https://aishotflow.cn/mcp" } } }

VS Code（1.99+）

在项目根目录创建 .vscode/mcp.json：

"servers": { "shotflow": { "type": "http", "url": "https://aishotflow.cn/mcp" } } }

Cline / Roo-Cline

编辑 ~/.cline/mcp_settings.json：

"mcpServers": { "shotflow": { "url": "https://aishotflow.cn/mcp" } } }

调用示例

生成短视频分镜

告诉你的 AI 客户端：

用 shotflow 的 generate_storyboard 工具，帮我生成一个短视频分镜：一个创业者熬夜做产品的故事，3个场景，温情风格，9:16竖屏

AI 会自动调用 MCP Tool，返回结构化分镜结果。

查看可用创作类型

读取 shotflow 的 creative-types 资源，告诉我有哪些创作类型可选

Agent Card（A2A 协议）

其他 AI Agent 可通过以下 URL 自动发现 ShotFlow 的能力：

https://aishotflow.cn/mcp/agent-card

部署自己的实例

要求

Node.js 18+
ShotFlow Express Server 运行在 localhost:3003

安装

git clone https://github.com/YOUR_USERNAME/shotflow-mcp.git

cd shotflow-mcp

无需 npm install，零依赖

启动

# 开发模式

node shotflow-mcp-server.js

默认端口 3004

生产部署（systemd）

sudo cp shotflow-mcp.service /etc/systemd/system/ sudo systemctl enable shotflow-mcp sudo systemctl start shotflow-mcp

环境变量

变量	默认值	说明
`MCP_PORT`	`3004`	MCP Server 监听端口
`SHOTFLOW_API_URL`	`http://localhost:3003`	ShotFlow Express 地址
`NODE_ENV`	`development`	环境模式

架构

AI Client (Claude/Cursor/...)

↓ Streamable HTTP (JSON-RPC 2.0) Nginx :443 └── /mcp → ShotFlow MCP Server :3004 └── HTTP → ShotFlow Express :3003

协议: MCP 1.0（Streamable HTTP + SSE）
传输: JSON-RPC 2.0 over HTTP
依赖: 零外部依赖（纯 Node.js 实现）
SSE 支持: proxy_buffering off 配合 Nginx 实现流式进度推送

文件结构

shotflow-mcp/

├── shotflow-mcp-server.js # MCP Server 主文件 ├── tool-definitions.js # 7个 Tool 的 JSON Schema 定义 ├── resource-definitions.js # 2个 Resource 定义 ├── prompt-builder.js # Prompt 构造与模型配置解析 ├── package.json # npm 包配置 ├── shotflow-mcp.service # systemd 服务文件 ├── INTEGRATION.md # 详细接入文档 ├── README.md # 本文件 └── test/ └── test-mcp.js # 测试套件

测试

# 启动本地服务

node shotflow-mcp-server.js &

运行测试

node test/test-mcp.js

许可证

MIT License — 自由使用、修改和分发。

支持

GitHub Issues: https://github.com/YOUR_USERNAME/shotflow-mcp/issues
邮件: admin@aishotflow.cn

Shotflow MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Aiterm MCP

README from the maker

ShotFlow MCP Server

在线使用

功能一览

快速接入

Claude Desktop

Cursor IDE

VS Code（1.99+）

Cline / Roo-Cline

调用示例

生成短视频分镜

查看可用创作类型

Agent Card（A2A 协议）

部署自己的实例

要求

安装

无需 npm install，零依赖

启动

默认端口 3004

生产部署（systemd）

环境变量

架构

文件结构

测试

运行测试

相关链接

许可证

支持