プロトタイプ · プレビュー版:公式レジストリのすべてのサーバーを掲載し、30分ごとに同期しています。レビューとアカウント機能は今後のステップで始まります。
PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

katra

作者:craigjmidwinterバージョン 0.1.0i★ –iパソコンで動く
レジストリ名io.github.craigjmidwinter/katra

インストール

概要

作者による説明(英語の原文)

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

PopNx MCPの3つの柱

この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。

できること

このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。

  • 接続方法: パソコンで動く
  • トランスポート: stdio
  • カテゴリ: 文書・表計算・事務作業

インストール

使っているAIアプリを選んで、設定をコピーしてください。

インストールの前に

  • 基本チェック:1項目中1項目に合格
  • あなたのパソコンで、あなたのユーザーと同じ権限(ファイル、ネットワーク、アプリ)で動きます。
  • レジストリには、入力が必要なキーは載っていません。

必要なもの

  • DockerDockerのインストール

どのアプリを使っていますか?

上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。

Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます

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

ターミナルでこれを実行します

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

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

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

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

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

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。

選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。

この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。

できること

パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。

基本チェックi

誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック

  • ✓ 合格

    作者とリポジトリが一致

    レジストリ名は、リポジトリを所有するGitHubアカウント craigjmidwinter で確認済みです

  • … 未チェック

    今もメンテナンスされている

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    ライセンスがある

    このリポジトリはまだGitHubから読み取っていません

  • – 対象外

    エンドポイントが応答する

    これはパソコンで動くため、インターネット上のエンドポイントはありません

  • – 対象外

    OAuthでサインイン

    パソコンで動き、代わりにローカルの設定を使います

  • … 未チェック

    ツールの説明に隠れた指示がない

    パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです

文書・表計算・事務作業のほかのサーバーとの比較i

  • このカテゴリのほかの2188件のうち0%よりスターが多い
  • このカテゴリのほかの2188件のうち30%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの2188件のうち100%と同じかそれ以上

レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。

よくある質問

katraは安全ですか?

当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。

どんなキーやコードが必要ですか?

レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。

パソコンで動きますか、それともクラウドですか?

あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は–、最新バージョン(0.1.0)がレジストリに届いたのは2 か月前です。

どのアプリで使えますか?

Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにDockerも必要です。

代わりに使えるものは?

同じカテゴリには:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

代わりの候補

同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。

カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i

Excel MCP Server

作者:haris-musa

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

パソコンで動く★ 4,276MIT6 日前更新
インストール

MCP Server for Excel

作者:sbroenne

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

パソコンで動く★ 847MIT3 日前更新
インストール

作者のREADME

READMEを開く

作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。

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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