comfy-ae-video-factory-mcp
Enables AI video automation pipeline: ComfyUI image-to-video, FFmpeg processing, After Effects template rendering, review, and multi-platform publishing preparation.
README
Comfy AE Video Factory MCP
一个用于 AI 短视频自动化流水线的 MCP Server:把 ComfyUI 图生图/图生视频、FFmpeg 后处理、After Effects 模板包装、审核与多平台发布准备串起来。
设计目标:让 Cursor / Claude Desktop / ChatGPT MCP 客户端可以调用这些工具,自动完成「生成 → 包装 → 审核 → 导出 → 发布包」的流程。
能力
- 调用本地或云端 ComfyUI workflow
- 查询 ComfyUI 任务历史
- 使用 FFprobe 分析视频
- 使用 FFmpeg 转码、裁切、抽帧、拼接
- 生成 AE 自动替换素材 JSX 脚本
- 调用 aerender 渲染 After Effects 模板
- 创建标准化视频生产任务 manifest
- 生成抖音 / 小红书 / B站 / YouTube Shorts / TikTok 发布包配置
- 提供基础内容审核占位接口,便于以后接第三方审核 API
安装
npm install
npm run build
运行
npm start
在 MCP 客户端中配置
{
"mcpServers": {
"comfy-ae-video-factory": {
"command": "node",
"args": ["/absolute/path/comfy-ae-video-factory-mcp/dist/index.js"],
"env": {
"COMFY_LOCAL_URL": "http://127.0.0.1:8188",
"VIDEO_FACTORY_ROOT": "/absolute/path/workspace",
"FFMPEG_BIN": "ffmpeg",
"FFPROBE_BIN": "ffprobe",
"AERENDER_BIN": "/Applications/Adobe After Effects 2025/aerender"
}
}
}
}
Windows 示例:
{
"AERENDER_BIN": "C:\\Program Files\\Adobe\\Adobe After Effects 2025\\Support Files\\aerender.exe"
}
推荐工作流
pipeline_create_job创建生产任务目录和 manifestcomfy_submit_workflow提交 ComfyUI 图生视频 workflowcomfy_get_history查询结果media_probe检查视频规格ffmpeg_transcode统一比例、码率、帧率ae_generate_jsx生成 AE 模板替换脚本ae_render_template调用 aerender 输出最终包装视频review_video_package做审核占位platform_prepare_package生成各平台发布包
AE 模板接入方式
推荐在 AE 工程里预先创建这些占位层:
{{MAIN_VIDEO}}{{TITLE}}{{SUBTITLE}}{{LOGO}}{{CTA}}
然后用本项目生成的 JSX 替换素材和文字,再通过 aerender 输出。
安全说明
这个 MCP Server 会执行本地命令,因此默认限制:
- 所有输入输出文件必须在
VIDEO_FACTORY_ROOT目录下 - FFmpeg 参数走白名单化封装,而不是直接暴露任意 shell
- AE 渲染支持
dryRun,建议先测试命令
GitHub 上传
git init
git add .
git commit -m "init comfy ae video factory mcp"
git branch -M main
git remote add origin git@github.com:YOUR_NAME/comfy-ae-video-factory-mcp.git
git push -u origin main
备注
MCP 官方 TypeScript SDK 支持创建 server、注册 tools,并通过 stdio 或 Streamable HTTP 连接 MCP 客户端。这里使用 stdio,适合本地自动化集成。
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