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

Skylos

作者:duriantacoバージョン 3.5.10i★ –iパソコンで動く
レジストリ名io.github.duriantaco/skylos

インストール

概要

作者による説明(英語の原文)

Dead code, security, secrets detection and code quality for Python, TypeScript, Go.

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: その他
  • 入力が必要なもの:SKYLOS_API_KEY

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

「秘密」と表示された値は、あなたのアカウントの鍵です。絶対に人に教えたり、チャットに貼り付けたりしないでください。

必要なもの

  • PyPIPythonのuvのインストール(uvxコマンドに必要)

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": {
    "skylos": {
      "command": "uvx",
      "args": [
        "skylos"
      ],
      "env": {
        "SKYLOS_API_KEY": "your-value"
      }
    }
  }
}

ターミナルでこれを実行します

claude mcp add skylos --env SKYLOS_API_KEY=your-value -- uvx skylos

動かす前に、空欄の値を入力してください。

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": {
    "skylos": {
      "command": "uvx",
      "args": [
        "skylos"
      ],
      "env": {
        "SKYLOS_API_KEY": "your-value"
      }
    }
  }
}

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": {
    "skylos": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "skylos"
      ],
      "env": {
        "SKYLOS_API_KEY": "your-value"
      }
    }
  }
}

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。

自分で入力する値

  • SKYLOS_API_KEY 秘密 env
    Skylos API key for cloud features and MCP authentication

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 duriantaco 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32564件のうち0%よりスターが多い
  • このカテゴリのほかの32564件のうち4%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32564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

Skylos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?

入力が必要なもの:SKYLOS_API_KEY

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(3.5.10)がレジストリに届いたのは8 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Python (uv)も必要です。

代わりに使えるものは?

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

Tools MCP

作者:First-CH

Web production tools for AI agents: contrast, JP text, WebP, JSON-LD, slugs, dates and 40+ more

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。

Skylos Code checks that show their work.

What Is Skylos?

Skylos is an open-source (Apache-2.0) CLI and pull-request gate for Python projects that runs without an account. skylos . finds dead code: unused functions, classes, imports and empty files. Add -a to check security bugs, hard-coded secrets, vulnerable dependencies, code quality and AI-code mistakes. Findings include source locations and supporting analysis; skylos done checks whether a branch, often a coding agent's, is ready to merge.

It is built for:

  • Teams merging pull requests from AI coding agents such as Claude Code, Codex and Cursor. skylos done runs your tests and flags deleted or skipped tests, loosened CI test steps, silenced lint or type checks, and test-only special cases.
  • Python maintainers who want framework-aware dead-code, security and secrets checks. Python has the deepest coverage; other languages are listed under Language Support.
pip install skylos

skylos . # find dead code skylos . -a # add security, secrets, quality, dependency and AI-code checks skylos done --base main # is this branch finished? runs your tests, compares with main

Working with a coding agent? Two commands:

skylos setup   # once per repo: connects Claude Code and Codex, writes the PR check, maps the code

skylos open # every day: diagram of your code, what changed in plain English, every check run

Your agent runs the checks itself. The tutorial walks through a real session: the agent describes the code, makes a change, gets blocked and fixes it from Skylos's fix brief.

Proof, including the misses: 10 Skylos-assisted dead-code cleanup PRs have been merged into the default branch in 9 open-source projects, including Black, NetworkX, Optuna, mitmproxy and pypdf. Real-World Results lists the 26 cleanup and quality-fix PRs in this ledger, including the ones that were closed, reverted or never reached the default branch. These are accepted cleanup PRs, not endorsements.

Website | Docs | Repo Map | Quick Start | GitHub Action | VS Code Extension | Real-World Results | Benchmarks | Roadmap | Contributing

English | Deutsch | 简体中文 | Translations

Skylos runs locally by default and can also gate pull requests in CI. Use it when you want one command to check a repo or pull request for:

  • dead code and unused files
  • security flaws and dangerous data flows
  • secrets and dependency CVEs
  • CI/CD and edge-device deployment misconfigurations
  • quality regressions such as complexity, duplicate branches, and deep nesting
  • common AI-generated code mistakes, including missing guards, fake helpers, invented package APIs, and impossible dependency versions
  • LLM app risks such as unsafe tool use and missing output validation

Skylos supports 12 languages: Python, TypeScript/JavaScript, Java, Go, PHP, Rust, Ruby, Dart, C#, C++, Kotlin and Shell. Python has the deepest coverage. TypeScript/JavaScript and Java also get dead-code, security and quality checks; PHP and Dart get dead-code and security checks (PHP security follows request data within a function or file into command and code execution, file inclusion, HTML output, SQL, SSRF, deserialization and file paths; Dart security covers command injection, path traversal and SSRF); Rust gets command-injection and path-traversal checks and experimental dead code (hidden below the default confidence threshold; --confidence 40 lists it). Go dead-code and security checks need the native skylos-go engine: from 4.50 the PyPI wheels for Linux, macOS and Windows (x86_64 and arm64) include it, the container image includes it and the GitHub Action builds it. On other platforms skylos doctor prints the command that builds it from source, and SKYLOS_GO_BIN points Skylos at a separately built engine. C# support is partial, Kotlin dead code covers only private declarations and imports (Kotlin security covers Spring, Ktor, servlet and Android WebView basics), C++ is limited to unused file-local functions, and Shell gets security checks only. Ruby adds bounded private-method liveness, literal Rails controller callbacks and explicit Kernel command checks. Skylos also checks CI/CD, deployment config and two Terraform/AWS declaration policies. See Language Support.

Read The Results

Remember Risk, Maintainability, Dead code, Gate:

ReadoutWhat it tells you
RiskHighest unresolved severity and counts. One critical finding stays critical, regardless of repository size.
MaintainabilityAdvice counts, affected code units, and how far measurements exceed their limits.
Dead codeRemoval candidates with confidence and evidence; review dynamic calls and public APIs before deleting.
GateWhether findings satisfy your configured limits. Passing means within policy, not zero findings.

Finding Type is separate from severity: Defect is a concrete correctness pattern, Review needs context, and Advice concerns maintainability or tooling. A Review finding can still be critical. Advice stays visible in rule groups; --expand-advice shows every location and JSON keeps complete records. Grouping cannot improve the assessment or bypass a gate.

Security findings show recorded source-to-sink evidence when available, with partial static analysis labeled. Dependency coverage names unresolved versions and the supported inputs needed to check them. Neither view claims runtime exploitability or a complete installed environment; JSON keeps the full evidence.

For uv.lock, Cargo.lock, composer.lock, Gemfile.lock and pubspec.lock, valid Git, URL, path and private-registry dependencies are shown as not checked. Skylos still queries supported public packages; the coverage gap alone does not cause exit 2. It cannot establish a clean dependency assessment. See uv source coverage.

New source scans replace the blended A–F grade with these readouts. Disabled checks are not assessed; failed checks are incomplete. Maintainability percentages use only the relevant units actually measured, with no guessed denominators or uncalibrated grades. The independent debt and defend scores keep their meanings. See the output guide.

Choose the Right Command

Each command answers a different question. The source scan requires PATH. Bracketed paths on verify, suite, defend, and clean default to the current directory. suite and defend require a directory; verify and clean also accept a file.

QuestionCommandInput checked
What problems are in this source tree?skylos PATHSource files and project configuration; dead code by default, every main source analyzer with -a
How is this branch doing on Skylos Cloud?skylos cloud [PATH]Every main source analyzer, then the findings are uploaded and the branch's quality gate is printed with one link
Did the agent really finish this branch?skylos done --base mainThe branch's changes since its merge base with main: Skylos runs your tests (pytest automatically; other runners need test_command in [tool.skylos.done]) and compares the tests, test settings and CI steps with the base; writes a receipt to .skylos/receipts/
What does this change touch, and what should I read first?skylos done map --base mainEach changed Python or TypeScript/JavaScript function since the merge base, with old and new code, calls added and removed, its callers and removed security checks, sorted into read first, read, skim and skip (skip only when the logic is proven the same); computed from the code, so the same commit gives the same map
Does this code contain AI-code mistakes?skylos verify [PATH]AI-defect checks over the selected file or tree, plus a separate Git HEAD behavior comparison for supported Python working changes
Should a model review static dead-code findings?skylos agent verify [PATH]LLM by default; optional Jev-only or Jev-plus-LLM review
What do I tell my CTO?skylos report [PATH]Every main source analyzer locally, then one self-contained HTML page (or --format md): verdict, top five risks with fixes, issue counts, coverage gaps, scan date, commit and version
What does the combined repo suite report?skylos suite [DIRECTORY]Static analysis, technical debt, AI app safety, and provenance; local findings are report-only by default
Does an agent implementation have deployment guardrails?skylos defend [DIRECTORY]Recognized Python and TypeScript/JavaScript LLM integrations; gating requires a threshold flag or policy
Which Python dead code can Skylos remove?skylos clean [PATH] --dry-runPython import/function cleanup candidates; --dry-run never writes
Will this exact local GPU build fit the machines we ship to?skylos preflight [ARTIFACT]A local built file or directory and .skylos/gpu-targets.yml; an OCI reference is identity-only and returns UNKNOWN in the CLI
What vulnerabilities are in this container image?skylos image scan IMAGE@sha256: --platform os/archA remote registry image scanned by a separately installed Trivy; --fail-on turns findings into a gate

Run skylos --help for this chooser, skylos --help for one command, and skylos commands for the command-family map.

The report commands have different gate and network behavior:

  • image scan requires Trivy on trusted PATH and uses Trivy's remote image source, so registry network access and any required registry credentials must already be available. Without --fail-on, a completed scan exits 0 even when it reports vulnerabilities.
  • suite runs in the local process and does not upload unless --upload is set, but its dependency scan can query OSV. Findings are report-only: the command exits 0 regardless of their count. Operational and output failures are nonzero; --upload can also fail for an upload error or Cloud quality gate.
  • defend reports guardrail findings by default. It becomes a gate with --fail-on, --min-score, or gate settings in an explicit policy.
  • clean without --dry-run or --apply is interactive and can write after the final confirmation. Its current codemods support Python imports and functions. An apply pass still exits 0 if an individual edit prints a failure, so review the completion output.
  • done exits 0 on pass, 1 when a blocking check fails or does not finish, and 2 when Skylos could not run (for example, the base is not fetched). It reads its settings from the base commit, so a

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