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

KittyClaw

作者:Ekiooバージョン 0.16.0i★ –i–
レジストリ名io.github.Ekioo/kittyclaw

インストール

概要

作者による説明(英語の原文)

Drive KittyClaw, a self-hosted agent-fleet kanban, from any MCP client (embedded /mcp endpoint).

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: –
  • トランスポート:
  • カテゴリ: その他

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。

作者はレジストリにインストール情報を載せていません。下にある作者のREADMEをご覧ください。

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6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 Ekioo 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

その他のほかのサーバーとの比較i

  • このカテゴリのほかの32509件のうち0%よりスターが多い
  • このカテゴリのほかの32509件のうち26%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32509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

KittyClaw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(0.16.0)がレジストリに届いたのは3 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。

代わりに使えるものは?

同じカテゴリには:Spec Driven Development, Remote Desktop Commander, Fomu MCP

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

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

クラウドで動く★ 211昨日更新
インストール

Fomu MCP

作者:gabrielmahia

Kenya government form guides: checklists, draft letters, eCitizen, Huduma, timelines. Sample data.

パソコンで動く今日更新
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。

KittyClaw

kittyclaw.dev · Get early access

KittyClaw is a local control plane for software work performed by AI agents. Submit a software ticket, watch it move across the live board, read the run that changed the code, inspect its verification evidence, and make the final release decision yourself.

The product proves three things in one journey: a live board, a readable run, and human validation before external release. New boards start with Backlog, Todo, InProgress, Blocked, Scheduled, Review, and Done (columns remain customizable). Runs can use Claude Code, OpenAI Codex, Grok Build, or a local Ollama model.

Follow the guided five-minute demo to repeat the journey with a realistic software ticket. The companion activation test protocol measures whether qualified trial users reach their first run within ten minutes.

A project can be split into independently named pipelines whose stable identities survive renames. Columns can own generic processors with persistent memory, reusable project skills, ordered ticket selection, durable retries, and switch-like routing to columns in any pipeline. Right-click a column and choose Configure column to edit its name, color, role, position, ticket guidance, processor, and routing without losing the visual context of the board. Tickets in Waiting or OwnerAction columns always show a prominent contextual block between their description and activity, explaining whether the owner must comment or move the ticket to a specific validation/refusal column, or whether KittyClaw will resume it automatically. Columns can also be inserted between existing lanes or added at the end directly from the Kanban; the Workflows page remains the global pipeline-and-skills overview. Execution state is separate from business columns, so an InProgress column is optional. Recurring work uses column scheduled tasks. Agents run through Claude Code, OpenAI Codex, Grok Build, Mistral Vibe, or a local Ollama model while their output streams into the app.

Each processor is versioned with its project in .agents/processors/column- /processor.json. This authoritative definition contains its mission, explicit prompt, model, skills, ticket ordering, retry policy, and routing. SQLite keeps only a synchronized runtime projection and execution state. Persistent lessons live beside the definition under .agents/processors/column- /memory/MEMORY.md.

Tech Stack

  • .NET 10 / Blazor Server (interactive SSR)
  • SQLite via Entity Framework Core (one DB per project)
  • OpenAPI with auto-generated Markdown docs
  • Agent execution: at least one supported CLI — [Claude Code CLI](https://docs.claude.com/en/docs/claude-code/overview), [OpenAI Codex CLI](docs/codex-cli.md), [Grok Build](docs/grok-build.md), or [Mistral Vibe](docs/mistral-vibe.md). [Ollama](https://ollama.com) and [DeepSeek V4](docs/deepseek.md) are supported through Claude Code. See the consolidated [agent-provider installation guide](docs/agent-providers.md).
  • Optional for repository initialization, worktree integrations, and agent commits: [Git](https://git-scm.com/downloads)

Getting Started

Windows installer

Download Ekioo.KittyClaw-win-Setup.exe from the latest release when that release includes the Windows installer. Run it, acknowledge the installation confirmation, then launch KittyClaw from its desktop or Start-menu shortcut. The Windows x64 installer includes the .NET, ASP.NET Core, and Windows Desktop runtimes; no SDK or separate .NET installation is required. Agent CLIs still need to be installed and authenticated separately (see the provider guide).

KittyClaw opens in your browser and stays in the notification area. Double-click its icon to open it again, or choose Quit KittyClaw from its menu to stop it. Installation is per user under %LOCALAPPDATA%/Ekioo.KittyClaw; project data stays in %APPDATA%/KittyClaw.

The update banner offers Download update, followed by Update and restart. Downloads do not interrupt work; installation is blocked while agent work or tracked finalization is active. See Windows packaging and updates for build and release details.

Run from source
Prerequisites
  • .NET 10 SDK
  • At least one agent CLI on your PATH: Claude Code (claude), OpenAI Codex (codex), Grok Build (grok), or Mistral Vibe (vibe). Local-model and DeepSeek execution use Claude Code as their transport; DeepSeek additionally requires DEEPSEEK_API_KEY in the project's secure vault.
  • Optional: Git (git on your PATH) for repository initialization, worktree integrations, and agent commits
  • Optional: Rust Token Killer (RTK) (rtk on your PATH) for explicit per-project shell-output optimization. KittyClaw never installs or configures it automatically and forces its telemetry off for opted-in runs.

On first launch, the onboarding popup checks Git and every supported provider CLI using the same resolved executable paths as dispatch: Claude Code (claude / KITTYCLAW_CLAUDE_BIN), OpenAI Codex (codex / KITTYCLAW_CODEX_BIN), Grok Build (grok, ~/.grok/bin, or KITTYCLAW_GROK_BIN), and Mistral Vibe (vibe / KITTYCLAW_MISTRAL_BIN). It also reports optional Ollama availability. Any one agent provider is sufficient, failed or timed-out probes remain non-blocking, and Git-dependent features still require Git.

Run

From the repo root:

run.bat        (Windows)

./run.sh (macOS / Linux)

Both wrap dotnet watch --project KittyClaw.Web --non-interactive and serve the app at http://localhost:5230 with hot reload enabled.

Creating a project

From the home page, select Create a project, enter a name, and choose its workspace. The built-in folder browser works on Windows, macOS, and Linux without opening a native system dialog behind the browser. It exposes the home directory, mounted drives or filesystem roots, breadcrumbs, parent navigation, and direct path entry. You can also type an absolute path and create the folder when it does not exist.

Click Initialize to:

  1. Create the project registry entry + per-project SQLite DB.
  2. Copy the project template from ProjectTemplate/ (preamble.md, {agent}/SKILL.md, {agent}/memory/MEMORY.md index, memory-consolidation.md, agent-budget.json, CLAUDE.md) into the workspace — agent files under /.agents/, CLAUDE.md at the workspace root.
  3. Run git init if the workspace is not already a git repo (skipped if git isn't installed).
  4. Create a member for each agent slug found in the template.
  5. Open the project setup wizard.

The setup wizard analyzes an existing workspace and proposes distinct pipelines, columns, human hand-offs, processors, routing, and schedules. For an empty folder it first asks a few questions about the project's purpose, deliverables, human decisions, and recurring work. Proposals are graphical: you can add or remove pipelines, review each pipeline's columns, refine a step with a prompt, and move backward before approval. Nothing is created during this preparation; Create the workflow applies and verifies the approved plan, then opens the board.

Existing pipelines can be refined through Edit with assistant. The legacy automation engine and its migration wizard are retired.

The workspace folder itself is never deleted by KittyClaw, even when you delete a project.

Data Storage

All KittyClaw data is stored locally in %APPDATA%/KittyClaw/:

  • registry.db — project registry
  • projects/{slug}.db — per-project database (tickets, comments, labels, columns, members)
  • uploads/ — uploaded images
  • runs/{runId}.json — agent run snapshots (events, status, exit code)
  • settings.json — language + onboarding flag

Per-project agent state lives in the workspace: /.agents/{agent}/memory/ (scored MEMORY.md index + per-topic lesson files), /.agents/channel/ (session state), etc.

Project Structure

PathDescription
KittyClaw.CoreDomain models, EF Core contexts, services, column workflow engines, embedded project template
KittyClaw.Core.TestsxUnit tests (processors, scheduling, agent execution, API, storage)
KittyClaw.WebBlazor Server UI + REST API
KittyClaw.QaRunnerIsolated test-instance launcher (Playwright + scenario runner) used by the qa-tester agent
KittyClaw.ClaudeMockMock claude CLI used by KittyClaw.QaRunner for hermetic agent dispatch in tests
ProjectTemplate/Source of truth for new-project initialization. Files under Agents/ are written to /.agents/; CLAUDE.md is written to the workspace root.
tools/Repo helpers (e.g. publish-stable.ps1 to bundle Web + QaRunner + ClaudeMock for a stable channel)

Architecture

Per-feature architecture documentation lives under docs/. Start with pipeline and column processing for the multi-pipeline model, or docs/index.md for the complete architecture map.

API

All endpoints are under /api. The documentation is auto-generated from the live OpenAPI spec:

  • Human-readable Markdown: GET http://localhost:5230/api/docs
  • Machine-readable JSON: GET http://localhost:5230/openapi/v1.json

MCP server

KittyClaw can expose an embedded MCP endpoint at http://localhost:5230/mcp (Streamable HTTP), so MCP clients can manage projects, tickets and acceptance criteria, configure column workflows and scheduled tasks, supervise agent runs, and handle approvals and worktree integrations. Open Settings from the home page and enable the MCP server, then hook it up to Claude Code with:

claude mcp add --transport http kittyclaw http://localhost:5230/mcp

The server exposes 73 tools: nine board and acceptance-criteria tools plus 64 management and observability tools. Reconnect clients after upgrading to refresh their tool catalogue. The endpoint is disabled by default, can be toggled without restarting KittyClaw, and uses the same localhost trust boundary as the REST API. See the complete tool catalogue and operation conventions.

For AI Agents

This app is designed to be operated by AI agents through its REST API. Here's how to get started:

  1. Read the live API docs at http://localhost:5230/api/docs — every endpoint, request/response example, and schema, always up to date with the running server.
  2. Identify yourself — author is required on every mutating endpoint; omitting it returns HTTP 400. Use your plain agent name (e.g. "programmer", "groomer"). The human user is "owner".
  3. Discover the board — call GET /api/projects first, then GET /api/projects/{slug}/columns to learn the workflow stages and GET /api/projects/{slug}/members for assignable members.
  4. Use the right status — ticket statuses must match existing column names. Fetch columns before moving tickets.
  5. Track your work — add comments on tickets to explain what you did or what you need. Use @mentions to notify members, #id to reference tickets in the same project, and #{slug}:{id} to reference tickets in another project.
  6. Labels & priority — use GET /api/projects/{slug}/labels to discover available labels, and set priority to Idea, NiceToHave, Required, or Critical.
  7. Check mentions — call `GET /api/projects/{

冒頭だけを表示しています。続きはリポジトリで読めます

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