Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@pm-workbench Process the latest meeting recording and update the PRD"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
一句话定位：给产品经理的开源 AI 工作台——会议录音进来，原型/PRD/评审记录出去，Agent 有手、有记忆、还会自己造工具。
产品经理 80% 的时间耗在"搬运"上：开会记纪要、回来整理成需求、写 PRD、画原型、跟踪评审——每个环节都在重复输入。PM Workbench 把这条流水线交给一个 53 工具的 AI Agent：
会议录音（小程序实时转写）
→ AI 总结 + 自动提取需求改动点
→ 一键变更原型（Agent 直接改 HTML）
→ PRD 同步更新 → 评审记录自动留档
→ 需求全流程可追踪Related MCP server: ProduckAI MCP Server
能力 | 说明 |
🎙 会议闭环 | 小程序录音实时转写 → AI 总结 → 需求改动点提取 → 一键派原型 Agent 修改 |
🤖 53 工具 Agent | 主 Agent 编排 + 5 个专业子 Agent（原型/PRD/调研/评审/周报） |
🛠 自造工具（创造模式） | 跟 Agent 说"造一个工具"，它自己创建并立即使用——借鉴 DeepSeek Harness |
🧠 越用越聪明 | Reflexion 教训回灌 + Voyager 成功打法库 + Mem0 式事实记忆 |
📋 六环 SOP | 一句"走完这个需求"，调研→原型→PRD→评审自动流转 |
📖 MCP 协议 | 53 工具按标准 MCP 暴露，Claude Code / Cursor 可直连 |
💰 成本账本 | 每轮对话 token 成本追踪（DeepSeek 约 ¥0.01/轮） |
📱 全端覆盖 | Web 工作台 + 微信小程序（录音/零散点捕获） |
Next.js 14 · TypeScript · DeepSeek（对话模型 + reasoner 双路由）· lowdb · 腾讯云 ASR · 微信小程序
git clone https://github.com/huangshu-jing/pm-workbench
cd pm-workbench
npm install
npm run dev
# 打开 http://localhost:3000，设置页填入 DeepSeek API Key 即可入口（Web / 小程序）→ Orchestrator 主 Agent（意图裁剪/分层提示词/上下文压缩）
→ 子 Agent 层（六环 SOP 流程引擎）
→ 能力层（53 工具 + 自造工具注册表）
→ 记忆层（事实抽取 + 向量检索）→ lowdb 数据层完整架构借鉴了 Pi Agent、OpenClaw、Mem0、MetaGPT、DeepSeek Harness 的设计，按垂类场景轻量化裁剪。
MIT
One-liner: An open-source AI workbench for PMs — meeting recordings in, prototypes/PRDs/review records out, with an agent that has hands, memory, and can even build its own tools.
PMs waste 80% of their time on "transporting" information: taking meeting notes, turning them into requirements, writing PRDs, drawing prototypes, tracking reviews. PM Workbench hands this pipeline to a 53-tool AI agent.
🎙 Meeting loop: record on your phone → live transcription → AI summary → extracted change points → one-click prototype edit by agent
🤖 Orchestrator + 5 specialized sub-agents (prototype/PRD/research/review/report)
🛠 Creation mode: say "build me a tool" and the agent creates and uses it immediately (inspired by DeepSeek Harness)
🧠 Gets smarter with use: Reflexion lesson injection + Voyager success-play library + Mem0-style fact memory
📋 Six-stage SOP: say "run this requirement end-to-end" and research→prototype→PRD→review flows automatically
📖 MCP protocol: all 53 tools exposed via standard MCP — connect from Claude Code or Cursor
Stack: Next.js 14 · TypeScript · DeepSeek (chat + reasoner dual routing) · lowdb · Tencent ASR · WeChat Mini Program
git clone https://github.com/huangshu-jing/pm-workbench && cd pm-workbench
npm install && npm run devMIT License
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