Show HN:一个将异步工作实践转化为工具的 MCP 服务器
Show HN: An MCP server that turns async-work practices into tools

原始链接: https://github.com/open-and-async/mcp

**Open and Async MCP 服务器**将专业的异步工作实践直接集成到你的 AI 辅助编辑器中。通过将《Open and Async》手册中的原则转化为可操作的工具,它使团队能够在不离开开发环境的情况下简化协作流程。 主要功能包括: * **方法工具**:生成结构化的决策文档(ADR)、将会议内容转化为异步工件、为状态更新评分以提高透明度,并促进异步站会。 * **决策支持**:使用“分类”功能来确定任务最适合同步还是异步处理,并提供相应的理由。 * **参考工具**:访问《Open and Async》一书的原则,搜索针对常见异步异议的反驳意见,并获取针对特定角色的指导。 * **“教练”提示词**:一个综合性工具,可用于评估复杂情况、起草相应的文档,并提供可分享的摘要。 该服务器被设计为一种实用工具而非营销工具,它提供带有引用和模板的输出,旨在帮助团队“公开工作”(work loudly)并减少不必要的会议。它兼容任何符合 MCP 标准的客户端(如 Claude Desktop 或 Claude Code),并确保你的工作流程保持结构化、文档化且高效。

GitHub 远程办公实践老兵 Ben Balter 推出了一款开源的**模型上下文协议(MCP)服务器**,旨在帮助团队转型为异步工作流。 受其相关新书的启发,Balter 开发了这一工具,旨在为静态文档提供一种交互式的 AI 驱动替代方案。用户无需仅依赖查阅手册,而是可以将该服务器集成到 Claude 等 AI 助手之中,从而获得针对特定工作挑战的个性化指导。 该 MCP 服务器包含多种专用工具,例如: * `draft_decision_doc`:自动生成决策文档。 * `convert_meeting_to_async`:将会议议程转换为异步格式。 * `score_status_update`:分析并提升沟通清晰度。 * `triage_sync_vs_async`:协助确定特定任务的最佳沟通模式。 该工具免费且开源,任何人都可以通过 `npx -y @open-and-async/mcp` 进行安装。Balter 将此项目描述为一场在 AI 时代下优化职场指导的实验。
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原文

Open and Async MCP Server — async-first working practices as tools your AI assistant can use

Bring async-first working practices into your editor and AI assistant. This Model Context Protocol server gives your AI the tools to draft a decision doc, turn a meeting into an async artifact, pressure-test a status update, or settle a sync-vs-async debate — without leaving the tools you already work in.

It's the method from Open and Async — the collaborative software-development playbook for remote and distributed teams — as working tools, not reading.

  • Stop writing decision docs from a blank page. Hand your AI the decision and the options; get back a structured ADR scaffold — context, tradeoffs, the call, and how reversible it is.
  • Turn "let's hop on a call" into an artifact. Give it a meeting's purpose and agenda; get the async equivalent with an owner and a deadline.
  • Ship status updates that don't blindside anyone. Score a draft against the "work loudly / no surprises" rubric and get concrete fixes before you post it.
  • Settle sync vs. async in seconds. Describe the task; get a recommendation and the rule behind it.
  • Run a standup without a meeting. Drop in a structured async-standup template your team can adopt today.
  • Win the "async is too slow" argument. Map common objections to a ready reframe, pull role-aware guidance, or search the book's principles — each answer cited and linked.
  • Get coached end to end. Run the coach prompt with a situation and it triages sync vs. async, generates the right artifact, adds role guidance, and caps with a shareable line — one composed answer, or a nudge to just have the conversation when that's the better call.

Claude Code:

claude mcp add open-async -- npx -y @open-and-async/mcp

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "open-async": {
      "command": "npx",
      "args": ["-y", "@open-and-async/mcp"]
    }
  }
}

Any MCP client that speaks stdio works the same way: run npx @open-and-async/mcp.

Method tools — pure utility, use them on any project

Tool What it does
draft_decision_doc Decision + options → a structured ADR/decision-doc scaffold (context, options, tradeoffs, decision, reversibility).
convert_meeting_to_async Meeting purpose/agenda → the async equivalent (artifact, owner, deadline).
score_status_update Scores a draft update against the "work loudly / no surprises" rubric and suggests fixes.
run_async_standup A structured async-standup template a team can adopt.
triage_sync_vs_async Recommends sync vs async for a task, with the decision rule.

Reference tools — the book's thinking, on demand

Tool What it does
book_outline Sections + chapters + one-line TL;DRs. The map.
get_chapter_summary A chapter's TL;DR + taglines + read-the-chapter link.
search_principles Keyword search over the summary corpus; short cited snippets.
handle_objection Maps skepticism ("async is slow") to the book's reframe.
get_guidance Role-aware (manager/ic) guidance for a topic.
get_taglines Taglines + their /q/<slug> quote-card URLs.
  • book://outline — sections, chapters, TL;DRs (JSON)
  • book://taglines — taglines + quote-card URLs (JSON)
  • book://about — what this server is, what it does and doesn't contain, and where to get the book

Invoke these directly from your client (e.g. as slash commands):

  • coachthe full method on one situation. Triages sync vs. async, generates the right artifact, enriches with role guidance, and caps with a shareable tagline — one composed deliverable. Stops and recommends a real-time conversation when the situation genuinely needs one.
  • async-standup, write-adr, meeting-to-issue, weekly-update — parameterized templates for a single task.

It's a real tool, not a paywall. The method tools work on their own — no book required. The reference tools answer from the book's already-public summaries and a paraphrased framework layer, always capped and always cited so you can trace any snippet to its chapter. The "get the book" link surfaces about once per session, not on every line — it's a tool, not an ad. No verbatim book prose is bundled (the only data file is data/book.json.br), so what you install is genuinely useful, not a teaser.

Staying current. data/book.json.br ships with a version that tracks the book's edition, so the server can tell you which edition it's based on and re-sync when a new one lands.

Generated output is a template, not the author speaking. The method tools format your input into decision docs, standups, and triage calls. That output is generated guidance to adapt — it is not a personal statement, quote, or endorsement by Ben Balter or Open & Async LLC, and shouldn't be presented as one. Reference-tool snippets are summaries the tool cites back to the book, not verbatim prose.

This package is split-licensed — see LICENSE for the overview:

  • Code (everything under src/) — MIT.
  • Data (data/book.json.br) — proprietary; © Open & Async LLC. You may use it only as part of running this software. No redistribution as a standalone dataset, no derivative datasets, no model training. See DATA-LICENSE.md.

The full work — the stories, the voice, the complete argument — lives in the book: open-and-async.com.

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