原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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katra

作者:craigjmidwinter版本 0.1.0i★ –i在你的电脑上运行
注册名称io.github.craigjmidwinter/katra

安装

概览

作者提供的说明(英文原文)

A committed markdown dev log and task graph that agents read and write over MCP.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 文档、表格与办公

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "katra": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/craigjmidwinter/katra-mcp:0.1.0"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add katra -- docker run -i --rm ghcr.io/craigjmidwinter/katra-mcp:0.1.0

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "katra": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/craigjmidwinter/katra-mcp:0.1.0"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "katra": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/craigjmidwinter/katra-mcp:0.1.0"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 craigjmidwinter 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“文档、表格与办公”中的其他服务器比较i

  • 星标数多于此分类中其他 2192 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2192 个服务器的 30% 更新
  • 基础检查结果等于或优于此分类中其他 2192 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

katra 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.0)于2个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Docker。

有什么可以替代它?

同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Agent-Native Calendar

作者:BuilderIO

Agent-Native Google Calendar - manage events, sync, and public booking

在云端运行★ 7,620MIT2个月前更新
安装

Excel MCP Server

作者:haris-musa

Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.

在你的电脑上运行★ 4,276MIT6天前更新
安装

MCP Server for Excel

作者:sbroenne

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

在你的电脑上运行★ 847MIT3天前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

katra

A committed, rich-component dev log you write as you build — for a developer working solo or alongside a coding agent — and the memory that makes spec-driven agentic development work. Markdown entries with embedded interactive components, stamped automatically with the commit and diffstat they describe, served as a live, auto-reloading page.

It exists to make one workflow reliable: *chronicle the work as it happens — the why, the dead ends, the screenshots and animations — and never lose a draft to a "promote" step that gets skipped.*

The same store is what keeps an agent effective across sessions: designs land as committed specs, tasks point at them, and a session starting cold reads the spec instead of re-deriving intent from a conversation that no longer exists. That loop is the agent workflow below.

katra init --install-hook        # store + portable Git auto-stamp

katra new "Reworked the swing" # start a draft (a markdown file) katra capture shot.png # drop a screenshot into it katra compare before.png after.png katra serve # live page on the LAN, reloads as you write git commit -m "…" # the draft is stamped with this commit

The one idea

A draft is an entry with no commit hash. That is the entire state machine.

It appears in the *In Progress* panel the moment you create it. There is no scratch file, no separate document, no "publish" toggle. Stamping it — adding the hash and the diffstat — is what drops it into the log.

Everything else follows from that. Nothing can get stranded in a buffer you forgot to promote, because there is no buffer. The log ends up in the order you actually worked, including the parts that did not pan out, which is the half a squashed history always loses.

The viewer

katra serve renders the store as a live page — no build step, no static site to regenerate while you write. The spine down the middle is the log in the order it happened: future epics, the entry in flight right now, then the past. The right rail surfaces what a flat file list buries — decisions that are still load-bearing, and which tags a stretch of work threads through.

More screenshots

An entry, open — this one shipped mid-draft with a before/after slider comparing two icon-mark directions, dragged in with katra compare:

The board, grouped by status — specced is its own column between todo and doing, for the tasks that have a committed design and nobody building them yet:

The hub, one page across every registered project on the machine — this is the maintainer's own, 14 projects and 25 things in flight at once, none of them re-typed anywhere:

The problem

You finish a hard week. The commits say fix streaming, wip, actually fix streaming. Six months later you need to know *why* the spawn budget is nearest-first, and the answer is not in the diff — it was in your head, and in a screenshot you no longer have.

The usual answers are all bad in the same way: they are a second job.

  • A CHANGELOG.md records what shipped, not what you learned, and it is written at release time from the diff you are trying to explain.
  • A wiki or a Notion page is not in the repo, so it drifts from the code immediately and is not there when someone clones.
  • A blog post is written afterwards, from memory — which is exactly when the detail you needed is gone.
  • Conventional commits give you a machine-readable *what* and no room for a *why*, a picture, or an alternative you rejected.

The common failure is that all of them are a step *after* the work, and any step after the work gets skipped when the work runs long — precisely when the log would have been worth most.

katra's bet is that the log has to be a side effect of working rather than a task that follows it. So the draft is created when you start, it accumulates screenshots and reasoning while you go, and the commit you were going to make anyway is what publishes it.

The agent workflow

This is what katra is built around, and the reason its shape is odd compared to a static-site generator: it exists to keep two things from being lost between agent sessions — the design an agent is meant to build from, and the record of how the build actually went.

An agent that logs at the end writes a summary of a diff — the one thing the diff already tells you. What is lost is everything before the final state: the approach that failed, the measurement that changed the plan, the picture of the bug. So katra pushes the log *into* the work. The common contract is the CLI sequence in The Katra workflow: declare the epic/task, attach and read a committed spec when one is warranted, open the draft before implementation, record decisions and evidence as you go, then stamp and close. It works from Codex, Claude Code, MCP, or a plain shell.

katra init --install-hook

That creates the Katra and installs the harness-neutral Git post-commit auto-stamp. Claude Code users can additionally run katra setup, which installs its skill and seven session hooks. With that optional adapter:

  1. `SessionStart` reports the active draft, unresolved memory, or in-flight changes that need reconciling.
  2. `PostToolUse` records every file the agent edits.
  3. `Stop` blocks the turn from ending if authored code changed and nothing declared what it was for.
  4. `PreToolUse` blocks a git commit whose staged code has no reconciliation receipt.
  5. Your commit fires the post-commit hook, which stamps the draft.

The gate is the part people react to, so it is worth being precise about when it fires. It blocks only when the turn authored code that is still present in the working tree, outside the katra directory, and nothing declared its purpose. A conversational turn never blocks. An edit-then-revert nets to nothing and never blocks. Someone else's pre-existing dirt is not your work and never blocks. A blocked turn never blocks twice for the same unchanged work.

To satisfy it — is a slug from katra task list (or create one with katra task new):

katra reconcile --advance <task>   # this moves a task forward

katra reconcile --close # this finishes one katra reconcile --no-task --reason "…" katra reconcile status # what does the gate want right now?

If you are trying katra out, use `katra setup --no-gate`. You get the nudges and the auto-stamp without anything blocking a commit, and you can turn the gate on later by re-running katra setup. A blocking hook in every repository is a real change to how committing feels, and it should be a choice made on purpose.

There is also an MCP server (katra-mcp) for clients that would rather call a tool than shell out. Its fifteen tools cover entries plus tasks, task specs, epics, decisions, and articles. Full detail: The Katra workflow and Agents.

When the first release ships, the official MCP Registry will be able to discover the same stdio server through a narrow OCI package. That image contains only katra-mcp and git; it exists because the registry needs an installable package, not because a container is a better way to use Katra. A registry client still has to expose the repository working tree to it. For direct use, install the native binaries above.

Spec-driven, not spec-derived

Current-source feature: the installed v0.1.0 CLI does not yet have

task spec, task new --spec, or the specced list-filter help value.

Build current source with make all for this phase until the next release;

the release checklist now asserts all three against the packaged binary.

A task can carry spec: — a node slug in the katra (a decision, an article, an entry) or a path relative to the repository root, resolved the same way as a [[wikilink]]. katra task spec attaches it, and moves the task from todo (or empty) to a new status, specced: *a design exists, committed, and nobody has started building it.*

katra task new "Cache swap"                           # todo, slug: cache-swap

katra decide "Cache invalidation: TTL, not events" # write the design katra task spec cache-swap cache-invalidation-ttl-not-events # by node slug katra task start cache-swap # -> doing, implement from it

The benefit is implementation efficiency and it compounds across sessions: an agent starting cold — new context window, different day — reads the spec instead of re-deriving intent from a conversation that no longer exists. katra task list --status specced is the worklist. Nothing requires a spec; todo → doing is still legal, and most tasks don't warrant one. specced is just a place to stand between "we should do this" and "someone is doing it," for the tasks where a design is worth writing down first — and the entries you write while implementing become the other half of the record: what the spec proposed against what actually happened, dead ends included.

Optional Claude Code memory ingest

Claude Code keeps native per-project memory. katra can ingest it into a private ledger, so the log gets the play-by-play without anyone re-typing it. Only metadata.type: project memories are admitted by default — not user (who you are), not feedback (how you like to be worked with), because neither belongs in a committed log. Anything matching a secret detector, or a term you list in sensitiveTerms, is quarantined rather than offered.

The ledger itself lives at katra/.state/memory-ledger.json and is deliberately local and gitignored — raw agent memory is unreviewed text about you and your machine, and it should never reach a shared branch by default; only the prose you choose to write from it does. So "review" means the katra memory scan | status | resolve | ignore queue *on the machine that produced it*: a teammate cloning the repo gets your entries, not your ledger.

Alternatives

Read this before adopting. Several tools do part of this, and some of them are a better fit than this one.

ToolUse it instead when

| Keep a Changelog + [release-please](https://gi

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