Puppetflow

com.puppetflow由 puppetflow.com 发布v1.0.0更新于 Oct 25, 2026

Build, run, monitor, and control Puppetflow browser automations from AI clients.

已验证Streamable HTTP可网页运行效率与工作流浏览器自动化

概览

AI 生成的概览

面向自托管 Puppetflow 实例的远程 MCP 服务器,让 AI 助手搜索、创建并运行浏览器自动化流程,并跟踪运行结果。

可以做什么
在工作区中搜索、查看和创建浏览器自动化流程及可复用片段,并手动或通过集成触发运行,可携带 JSON 输入。跟踪运行状态,查看运行历史、日志和执行结果。获取已完成运行的截图、文件和会话录制等产物。管理变量、密钥、浏览器配置文件以及作为流程输入的媒体库文件等配套资源。
适用场景
当你已运行自托管 Puppetflow 实例,并希望 AI 客户端在对话中编写、启动和监控 JavaScript 浏览器工作流时使用。适合需要人工介入、实时观看会话并保留运行历史的浏览器自动化团队。
运行要求
需要可访问的自托管 Puppetflow 实例(支持 Docker 部署),在 Workspace 设置中启用 MCP,并创建访问令牌,通过 Authorization Bearer 请求头发送;也提供带 PKCE 和动态客户端注册的 OAuth。不在本地运行任何内容,客户端通过 Streamable HTTP 连接实例的远程端点。
安装前请注意
该服务器可创建并运行浏览器自动化流程,会操作外部网站,可能提交表单或修改数据。它管理变量、密钥和浏览器配置文件,并可连接代码仓库和 1Password 等外部保险库,因此访问令牌等于对实例的广泛控制权。请将令牌视为机密并谨慎限定权限。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Puppetflow,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

[Puppetflow]

Puppetflow

Puppetflow is a self-hosted browser automation platform for writing, running, scheduling, and monitoring JavaScript workflows. Watch browser sessions live and take control whenever a run needs human attention.

[GitHub stars] [Package on GHCR] [GHCR package version] [Last commit]

⭐️ Like Puppetflow? Give the repository a star. It helps others discover the project.

Install Puppetflow with one command

curl -fsSL https://puppetflow.com/install.sh | bash

🌐 Website and documentation

🎉 Features

  • Build browser workflows in JavaScript
  • Run workflows manually, on a schedule, or through integrations
  • Watch browser sessions live and take control when needed
  • Organize flows and reusable snippets in workspaces
  • Store, tag, organize, and edit text files in a scoped Media Library, then reuse them in flow inputs or $upload
  • Manage variables, secrets, and browser profiles
  • Inspect run history, logs, and execution results
  • Connect repositories and external vaults like 1Password
  • Integrate with messaging tools and mailboxes
  • Deploy on your own infrastructure with Docker
  • Extend Puppetflow with reusable flows and snippets
  • Automate Media Library files and folders through the authenticated REST API

🔗 n8n integration

Puppetflow provides the n8n-nodes-puppetflow community node for adding browser automation to n8n workflows.

  • Trigger a flow with optional JSON input.
  • List and monitor runs, then retrieve their results.
  • Download screenshots, files, and session recordings.

Install the package from Settings > Community Nodes on a self-hosted n8n instance, then connect it with your Puppetflow instance URL and an API key from Profile > API Keys. See the n8n integration guide for setup details.

🤖 MCP server for AI clients

Every Puppetflow instance exposes a remote Model Context Protocol server over Streamable HTTP. Connect Cline, Cursor, Claude, Claude Code, or any other MCP client to search, inspect, create, and run browser automation flows, follow runs, and retrieve results, screenshots, and recordings.

Nothing runs locally. Enable MCP under Workspace > Settings > Instance MCP, create an access token, then add the endpoint to your client:

json
{  "mcpServers": {    "puppetflow": {      "type": "streamableHttp",      "url": "https://your-puppetflow.example/api/mcp-server/http",      "headers": {        "Authorization": "Bearer mcp_your_token_here"      }    }  }}

An OAuth endpoint with PKCE and Dynamic Client Registration is also available for clients that support remote MCP OAuth. See llms-install.md for step-by-step client setup and the MCP guide for the complete tool list.

Puppetflow in action

🛟 Discussion / Need help?

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Open an Issue

[Open an issue on GitHub]

Project philosophy

Puppetflow is built around a few straightforward ideas:

  • Browser automation should remain understandable and debuggable.
  • Self-hosting should be a real option, not an afterthought.
  • Good defaults matter, but users should keep control of their data and infrastructure.
  • Reliability and maintainability matter more than shipping a long list of half-finished features.

A note on project history

The public Git history was intentionally reset for the Community Edition release for security reasons. This repository's commit count therefore does not reflect the age or maturity of the project.

Puppetflow has been developed and operated in real conditions for nearly a year. The Community Edition is a publication of an existing product, not the beginning of a prototype.

No AI Slop Policy

Puppetflow does not accept low-effort, unreviewed generated code or content.

AI-assisted work is not banned. Submitting output that the contributor does not understand, has not checked, or cannot maintain is. Contributions must be deliberate, consistent with the existing codebase, and owned by the person submitting them.

See Contributing for the practical rules.

Repository documentation

License

Puppetflow is source available. Most of the code is licensed under the Puppetflow Source Available License, which permits personal, non-commercial use. Internal business use requires a current paid Puppetflow subscription or order.

Files under proprietary/, files containing the .pp. marker, and explicitly marked code blocks implement paid features. They are covered by the Puppetflow Proprietary License, and their use in production requires a valid Puppetflow subscription.

来源:README.md,提交 2d64e63

工具

0
SourceWeft 尚未读取此服务器的工具。

版本历史

1
  1. v1.0.0最新Sep 16, 2026

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