CLI Command Explainer MCP Server

@zmwaiworld

リポジトリ

基本情報

カテゴリ

開発者ツール

トランスポート

stdio

作者

zmwaiworld

投稿者

Zhenming Wang

CLI Command Explainer MCP Server について

Know what every shell command does before you approve it.

#security #cli #shell #developer-tools #coding-agent #command-line #risk-assessment

CLI Command Explainer MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "cmd-explain": {
      "command": "npx",
      "args": [
        "-y",
        "cmd-explain"
      ]
    }
  }
}

CLI Command Explainer MCP Server のツール

Explains a CLI command in one sentence. Returns the explanation, risk level (low/medium/high), and parsed command structure.

概要

What is CLI Command Explainer?

CLI Command Explainer is an MCP server that intercepts every shell command an AI coding agent proposes to run and displays a plain-English explanation with a risk rating before the user approves or denies it. It works with Kiro, Cursor, VS Code, Windsurf, and Claude Code.

How to use CLI Command Explainer?

Run npx cmd-explain setup — the command auto-detects your IDE, installs the MCP server, and creates a pre‑command hook. Restart your IDE and every agent‑proposed shell command will be explained automatically. Manual install by adding the MCP configuration is also supported.

Key features of CLI Command Explainer

Built‑in dictionary covering 240+ programs and 440+ command explanations
Falls back to system man pages for installed tools (Tier 2)
Optional local AI via Ollama, OpenAI, or Anthropic (Tier 3)
Risk classification: low (read‑only), medium (state‑changing), high (destructive)
Detects common shell patterns like 2>&1, || true, and command substitution
Supports macOS, Linux, and Windows with zero‑config setup

Use cases of CLI Command Explainer

Understanding what a complex agent‑proposed command actually does before approving it
Avoiding dangerous commands like rm -rf / or curl … | sudo bash
Learning the meaning of shell flags and redirections without leaving the flow
Adding a security layer to AI coding agents in team or production environments

よくある質問

What are the requirements to run CLI Command Explainer?

Node.js 18 or later is required. No API keys, no Ollama installation, and no configuration files are needed for the built‑in and man‑page tiers.

How does CLI Command Explainer get its explanations?

It uses three tiers checked in order: a built‑in dictionary (Tier 1, ~90% of agent commands), system man pages (Tier 2), and optional local AI via Ollama, OpenAI, or Anthropic (Tier 3). Tiers 1 and 2 are fully offline.

What does the risk classification mean?

Low risk means read‑only commands with no side effects. Medium risk means state‑changing but reversible operations. High risk means destructive or irreversible actions. Unknown risk is applied to commands not recognized by any tier.

Does CLI Command Explainer work on Windows?

Setup and the dictionary work on Windows. Man‑page parsing (Tier 2) uses `--help` only; the other tiers work fully.

How do I remove CLI Command Explainer?

Run `npx cmd-explain uninstall`. This removes the MCP configuration and hook files from all detected IDEs cleanly.

「開発者ツール」の他のコンテンツ

Modelglass

Modelglass turns "which model should I use?" into a lookup instead of a guess. Seven tools give your agent live pricing across image, language, video, and audio models. Sourced and versioned, not scraped once and forgott

Casefile

azimov777

One case file per task — shared by every session, agent and person that touches it. Self-hosted MCP server and live board. MIT.

Capgo MCP

Cap-go

Console, Backend and CLI to manage Capgo Instant update and Native build for Capacitor apps Build and upload to app store your mobile app

SSH MCP Server

hypnosis

SSH MCP server for AI agents: remote commands, file transfer, log search and server audits through OpenSSH.

ArtiBot Cloud MCP - Zhijiangyun 智匠云

bofob

ArtiBot Cloud MCP (Zhijiangyun 智匠云) — cloud MCP server for robot manipulation data & GPU workloads. 15 tools: robot fleet management, data collection & video recording, post-processing pipelines, and benchmark evaluation