This server provides functionality for visualizing and analyzing directory structures with customizable options:
Get deep directory tree: Retrieve the directory tree structure for a specified path.
Configurable depth: Customize the maximum depth of the directory tree (default: 3).
Pattern-based exclusion: Exclude specific directories or files using patterns (default exclusions: node_modules, .git, .turbo, dist, .next).
Absolute path support: Works best with absolute paths for accurate tree generation.
Required runtime for development of the MCP server
Required runtime environment for the MCP server, used to analyze and visualize directory structures
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@deep-directory-tree-mcp show me the project structure up to depth 3"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A powerful Model Context Protocol (MCP) implementation for visualizing and analyzing directory structures. Why? Now you can let AI assistants understand and navigate your project structure efficiently, enabling smarter code navigation and project organization insights.
Built with:
Deep directory tree visualization
Configurable depth-based tree generation
Smart pattern-based file/directory exclusion
Clean and readable tree output format
Real-time directory structure updates
Targeted directory analysis
DEMO:
Related MCP server: GitViz MCP
Node.js (v18 or higher)
The easiest way to get started is using Smithery:
npx -y @smithery/cli install @andredezzy/deep-directory-tree-mcp --client cursorOpen Cursor Settings → MCP → Add new MCP server
Configure with these settings:
{
"deep-directory-tree": {
"command": "npx",
"args": ["-y", "@andredezzy/deep-directory-tree-mcp"]
}
}Add the following to your MCP configuration:
{
"mcpServers": {
"deep-directory-tree": {
"command": "npx",
"args": ["-y", "@andredezzy/deep-directory-tree-mcp"]
}
}
}Common commands for AI assistants:
"Show me the directory structure"
"Visualize project tree up to depth 4"
"Show files excluding test directories"
Bun Runtime (required)
# 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 buildOpen Cursor Settings → MCP → Add new MCP server
Configure with these settings:
{
"deep-directory-tree": {
"command": "node",
"args": ["ABSOLUTE_PATH_TO_MCP_SERVER/bin/deep-directory-tree.js"]
}
}Add the following to your MCP configuration:
{
"mcpServers": {
"deep-directory-tree": {
"command": "node",
"args": ["ABSOLUTE_PATH_TO_MCP_SERVER/bin/deep-directory-tree.js"]
}
}
}Fork the repository
Create feature branch (git checkout -b feature/amazing-feature)
Commit changes (git commit -m 'Add feature')
Push to branch (git push origin feature/amazing-feature)
Open a Pull Request
Need help? Try these resources:
MIT License - see LICENSE file for details.
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.
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.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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