MCP Terminal Server
MCP ターミナルサーバー
セキュリティと制御を維持しながら AI モデルが端末と対話できるようにする、モデル コンテキスト プロトコル (MCP) 用の安全なコマンドライン インターフェイス サーバーです。
特徴
🔒 設定可能な権限による安全なコマンド実行
📁 許可されたパス内でのファイルシステム操作
🌍 環境変数の管理
💻 クロスプラットフォームサポート(Windows、macOS、Linux)
🔌 コマンド実行によるリモートシステム接続のサポート
Related MCP server: Shell MCP Server
Claude Desktopでの使用
Claude Desktop 構成ファイルにサーバー構成を追加します。
{
"mcpServers": {
"terminal": {
"command": "npx",
"args": [
"@dillip285/mcp-terminal",
"--allowed-paths",
"/path/to/allowed/directory"
]
}
}
}変更を適用するには、Claude Desktopを再起動してください。これで、Claudeのターミナル機能、安全なファイルアクセス、コマンド実行が使用できるようになります。
利用可能なツール
execute_command: ターミナルコマンドを安全に実行する(SSHおよびリモートコマンドを含む)
安全
すべての操作は指定された許可されたパスに制限されます
コマンドは実行前に検証され、サニタイズされます
環境変数は慎重に管理されます
セキュリティ関連の問題に対する適切なエラー処理
発達
# Clone the repository
git clone https://github.com/dillip285/mcp-terminal.git
# Install dependencies
npm install
# Configure npm authentication
cp .npmrc.example .npmrc
# Edit .npmrc and add your NPM_TOKEN
# Run tests
npm test
# Build the project
npm run build出版
パッケージを公開するには:
.npmrc.exampleを.npmrcにコピーします。npm認証トークンを
.npmrcに追加するnpm publish --access publicを実行します。
注意:認証トークンを含む.npmrcファイルをコミットしないでください。認証トークンは既に.gitignoreに追加されています。
貢献
リポジトリをフォークする
機能ブランチを作成します(
git checkout -b feature/amazing-feature)変更をコミットします (
git commit -m 'feat: Add amazing feature')ブランチにプッシュする (
git push origin feature/amazing-feature)プルリクエストを開く
ライセンス
MIT ライセンス - 詳細についてはLICENSEファイルを参照してください。
関連プロジェクト
サポート
バグ報告や機能リクエストについては、問題を開いてください。
Available Tools
1 toolexecute_commandC
Execute a command in the local system
| Name | Required | Description | Default |
|---|---|---|---|
| args | No | Command arguments | |
| command | Yes | Command to execute | |
| cwd | No | Working directory for command execution |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'execute a command' implies a potentially powerful/mutating operation, it doesn't disclose critical behavioral traits like security implications, permission requirements, side effects, error handling, or output format. This leaves significant gaps for an AI agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that directly states the tool's purpose without any unnecessary words. It's perfectly front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that executes system commands (a potentially dangerous operation with no output schema), the description is severely lacking. It doesn't address security implications, permission requirements, typical use cases, error handling, or what kind of output/result to expect. The absence of annotations exacerbates these gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description doesn't add any meaningful parameter semantics beyond what's already in the schema (command, args, cwd). This meets the baseline expectation when schema coverage is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('execute') and target ('a command in the local system'), providing a specific verb+resource combination. However, since there are no sibling tools mentioned, it cannot demonstrate differentiation from alternatives, preventing a perfect score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites, constraints, or typical use cases. It simply states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- First observed
execute_command
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'execute_command' has a clear and distinct purpose that cannot be confused with any other tool in this set.
The single tool name 'execute_command' follows a verb_noun pattern, and with only one tool, the naming is inherently consistent. There are no other tools to compare against, so no inconsistencies can arise.
A single tool for a terminal server feels too minimal for the apparent scope. While it covers basic command execution, typical terminal operations might include listing files, navigating directories, or managing processes, suggesting a gap in functionality.
The tool surface is severely incomplete for a terminal server domain. It only allows command execution, missing essential operations like file browsing, process management, or environment inspection, which are core to terminal workflows and will likely cause agent failures.
Maintenance
Related MCP Connectors
Operate Linux, macOS and Windows from your LLM. Every action runs through an auditable allowlist.
- emisarOAuthdev.emisar
Let AI operate servers without SSH. Choose actions, approve risky changes, and audit every step.
I run shell commands on your private cloud environment (bash, sh, zsh)
Real Linux labs your AI agent deploys, routes and runs, with domains, TLS, DBs and an audit log.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceA secure server that allows LLM applications like Claude to execute whitelisted system commands with user confirmation and comprehensive security features.-
- AlicenseBqualityFmaintenanceA secure server that enables AI applications to execute shell commands in specified directories, supporting multiple shell types (bash, sh, cmd, powershell) with built-in security features like directory isolation and timeout control.121Apache 2.0
- AlicenseAqualityFmaintenanceAn MCP server that enables secure terminal command execution, directory navigation, and file system operations through a standardized interface for LLMs.1034 PyPI97MIT
- AlicenseBqualityDmaintenanceA secure terminal execution server that enables controlled command execution with security features and resource limits via the Model Context Protocol (MCP).130 npm11MIT