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Lazycow Studio

Lazycow Studio

本地服务
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关于 Lazycow Studio

Lazycow Studio 的软件包让用户和 Agent 在本地工作室中用照片和视频制作、规划并发布短视频和旅行影片。发布前必须由人工批准。

主要功能

  1. 01制作和改编短视频
  2. 02规划并发布已批准内容
  3. 03研究创意和活动
  4. 04查看效果摘要
  5. 05安装并控制工作室
  6. 06Node.js API 和命令行

适用场景

  1. 01将未剪辑素材制作成短视频
  2. 02规划社交账号帖子
  3. 03为影片研究地点和活动

MCP 相关

其 MCP 服务提供控制本地 Lazycow Studio 的工具,包括制作短视频、研究、规划和发布已批准内容。Agent 无法批准内容;账号机密保留在工作室中。

配置

本地服务的配置在各客户端中通用,复制后粘贴到客户端的 MCP 配置文件即可。

mcp.json · 通用配置
{
"mcpServers": {
"kensaurus-lazycow": {
"command": "npx",
"args": [
"-y",
"lazycow"
],
"env": {
"STUDIO_PORT": "<STUDIO_PORT>",
"STUDIO_API_TOKEN": "<STUDIO_API_TOKEN>",
"LAZYCOW_DIR": "<LAZYCOW_DIR>"
}
}
}
}
启动命令npx -y lazycow
需要配置的环境变量
STUDIO_PORTThe studio's port (default: the studio's .env, else 4317)
STUDIO_API_TOKEN密钥The studio's API token, only if you set one (default: read from the studio's .env)
LAZYCOW_DIRThe studio folder, if it is not where the double-click setup put it

本地服务需要在你的电脑上安装运行环境(如 Node.js 18+)。各客户端的配置文件位置不同,请参考客户端文档。

安装包
npmlazycow0.14.1

工具

还没有获取到工具列表

本地服务需要在你的电脑上运行后才能读取工具,维护者暂未提供工具列表。

README 原文English

来自项目 README

README 暂无中文译文,以下为英文原文;中文介绍见上方。

lazycow

Lazycow Studio from the command line, from your AI agent and from your code.

Lazycow Studio turns the photos and videos you never edited into short vertical reels and YouTube trip films. It runs on your own computer, and a person approves every post. This package connects to it in three ways:

You want to…Run
Install the studio (no terminal skills needed after this line)npx lazycow install
Let Claude Code, Claude Desktop or Cursor drive itclaude mcp add lazycow -- npx -y lazycow mcp
Script it from Nodeimport { createClient } from "lazycow"

Approving a reel stays a person's job in the studio. Agents and scripts can make, plan and post approved reels. They cannot approve.

You watch the reel, press Approve, and it is booked on the posting calendar

Watch the 40-second demo · See the studio's pages

Install the studio

npx lazycow install

It downloads this version's release zip from GitHub, checks it against the SHA-256 built into the package, unpacks it to ~/Lazycow Studio, and starts the double-click setup. The setup installs Node, Python and ffmpeg for Lazycow only, in about 10 minutes. Options: --dir <empty folder>, --yes (take every suggestion).

Prefer to click? Download the zip from Releases, unzip it, read README.TXT, and double-click Start Lazycow.

Connect an AI agent (MCP)

Claude Code:

claude mcp add lazycow -- npx -y lazycow mcp

Claude Desktop or Cursor (claude_desktop_config.json / .cursor/mcp.json):

{
  "mcpServers": {
    "lazycow": { "command": "npx", "args": ["-y", "lazycow", "mcp"] }
  }
}

The server finds the studio by itself: STUDIO_PORT and STUDIO_API_TOKEN when set, else the .env in LAZYCOW_DIR, else the folder the setup recorded. So your agent config never holds a copy of the token.

The 27 tools ("reads" change nothing; "spends" means paid AI, priced first and kept inside the studio's limits):

AreaTools
The studiostudio_status, list_projects, switch_project, read_log (reads, except switching)
Reelslist_reels, reel_details, list_themes (reads); make_reels, make_reel, remix_reel (render in the background)
Jobsjob_status, cancel_job
Postinglist_posts, list_accounts (reads); plan_post, publish_reel, schedule_reel (approved reels only)
Researchresearch_ideas, research_events, research_page, research_site_check, research_links (reads the web through the studio; suggestions, never posted)
AI assistai_estimate, ai_review (reads); ai_run (spends, never changes an approved reel)
Resultsperf_summary, perf_suggest (reads)

Every tool, its inputs and examples: docs/mcp.md.

Each tool answers with a plain sentence and the data, and the same data as structuredContent for programs (a list arrives as { "items": [...] }). Account secrets never leave the studio.

Listed in the official MCP Registry as io.github.kensaurus/lazycow.

Use the API from code

import { createClient } from "lazycow";

const studio = createClient();            // or createClient({ port: 4318, token: "..." })
const health = await studio.health();
const { reels } = await studio.overview();
const anything = await studio.request("GET", "/api/posts");

Every route is in the studio's OpenAPI document. Errors are StudioError with status, path and body. Types are included.

From a shell:

npx lazycow status
npx lazycow api GET /api/posts
npx lazycow open

Requirements

Node 20 or newer. The studio itself runs on Windows 10/11 and macOS 14+ (Apple silicon); Linux works from source.

Credits and licence

Made by kensaurus (Kenji Sakuramoto, kensaur.us). Apache-2.0: if you redistribute it or build on it, keep the NOTICE file, and please keep the line "Based on Lazycow Studio by kensaurus". "Lazycow" and the sleepy-cow icon are trademarks of kensaurus LLC (TRADEMARKS.md).

Like it? Support Lazycow: supporters get their feature requests looked at first.

评论

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第一次接触 MCP?

从协议是什么,到在客户端里装上第一个服务,这几条回答覆盖了大多数入门问题。

一个开放协议,规定了 AI 应用如何以统一方式连接外部工具与数据源。客户端负责与模型对话,MCP 服务负责提供工具、资源和提示模板,两者通过标准消息通信,同一个服务可以被不同客户端复用。