ディレクトリ構造を視覚化および分析するための強力なモデルコンテキストプロトコル（MCP）実装。AIアシスタントがプロジェクト構造を効率的に理解・ナビゲートできるようになるため、よりスマートなコードナビゲーションとプロジェクト構成の洞察が可能になります。
搭載コンポーネント:
深いディレクトリツリーの視覚化
設定可能な深度ベースのツリー生成
スマートパターンベースのファイル/ディレクトリ除外
クリーンで読みやすいツリー出力形式
リアルタイムのディレクトリ構造の更新
ターゲットディレクトリ分析
デモ：
Related MCP server: MCP Filesystem Server
Node.js (v18以上)
始める最も簡単な方法は、 Smiseryを使用することです。
npx -y @smithery/cli install @andredezzy/deep-directory-tree-mcp --client cursorカーソル設定を開く → MCP → 新しいMCPサーバーを追加
次の設定を構成します。
{
"deep-directory-tree": {
"command": "npx",
"args": ["-y", "@andredezzy/deep-directory-tree-mcp"]
}
}MCP 構成に以下を追加します。
{
"mcpServers": {
"deep-directory-tree": {
"command": "npx",
"args": ["-y", "@andredezzy/deep-directory-tree-mcp"]
}
}
}AI アシスタントの一般的なコマンド:
「ディレクトリ構造を見せてください」
「深さ4までのプロジェクトツリーを視覚化する」
「テストディレクトリを除くファイルを表示する」
Bunランタイム（必須）
# Clone the repository
git clone https://github.com/andredezzy/deep-directory-tree-mcp.git
cd deep-directory-tree-mcp
# Install dependencies
bun install
# Build the project
bun run buildカーソル設定を開く → MCP → 新しいMCPサーバーを追加
次の設定を構成します。
{
"deep-directory-tree": {
"command": "node",
"args": ["ABSOLUTE_PATH_TO_MCP_SERVER/bin/deep-directory-tree.js"]
}
}MCP 構成に以下を追加します。
{
"mcpServers": {
"deep-directory-tree": {
"command": "node",
"args": ["ABSOLUTE_PATH_TO_MCP_SERVER/bin/deep-directory-tree.js"]
}
}
}リポジトリをフォークする
機能ブランチを作成する ( git checkout -b feature/amazing-feature )
変更をコミットする（ git commit -m 'Add 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
ヘルプが必要ですか？以下のリソースをお試しください。
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。
Get deep directory tree
| Name | Required | Description | Default |
|---|---|---|---|
| options | No | Tree generation options | |
| path | Yes | Path to get the directory tree (preferably absolute path) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the action without detailing output format, performance implications, error handling, or system impacts. This is inadequate for a tool that likely returns structured data and may have depth/exclusion constraints.
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 with a single phrase, front-loaded and without unnecessary words. It efficiently conveys the core intent, though this brevity contributes to gaps in other dimensions.
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?
Given no annotations, no output schema, and a tool with behavioral complexity (e.g., tree generation with exclusions), the description is incomplete. It fails to explain return values, error cases, or practical use, leaving significant gaps for agent understanding.
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?
Schema description coverage is 100%, so the schema fully documents parameters like 'path' and 'options' with defaults. The description adds no parameter semantics beyond what the schema provides, meeting the baseline for high coverage but not enhancing understanding.
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 'Get deep directory tree' states the basic action (get) and resource (directory tree), but lacks specificity about what 'deep' means or how it differs from a shallow tree. Without sibling tools, differentiation isn't needed, but the purpose remains vague about the nature of the operation beyond the literal interpretation.
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?
No guidance is provided on when to use this tool versus alternatives or any prerequisites. The description does not mention context like file system exploration or debugging scenarios, leaving the agent with no usage cues beyond the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0get_deep_directory_treeScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool's purpose is clearly distinct by default.
A single tool inherently follows a consistent naming pattern, as there are no other tools to compare against. The name 'get_deep_directory_tree' uses a clear verb_noun structure.
One tool is too few for a server named 'deep-directory-tree-mcp', which suggests a scope that might include operations like listing, filtering, or modifying directory trees. A single get operation feels thin and incomplete for this domain.
The tool surface is severely incomplete for a directory tree domain. It only provides a get operation, with obvious gaps such as creating, updating, deleting, or searching directory trees, which are essential for basic CRUD coverage.
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