# deep-filesystem-tree

> Use this tool when you need to efficiently navigate and manage complex directory structures, as it provides deep filesystem tree visualization and manipulation capabilities. It solves problems related to development workflow optimization, allowing for AI-powered file system operations. The tool takes directory structures as input and outputs a visual representation, enabling streamlined management of files and folders.

Canonical page: https://skillsregistry.net/skills/andredezzy-deep-filesystem-tree-mcp  
JSON: https://api.skillsregistry.net/v1/skills/andredezzy-deep-filesystem-tree-mcp

## Description

A Model Context Protocol (MCP) implementation that provides deep filesystem tree visualization and manipulation capabilities. This tool enables efficient navigation and management of complex directory structures, enhancing development workflows with AI-powered file system operations. Compatible with

## Trust

- **Trust score (0–1):** 0.95
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/yf735o30h1)
- **Repository:** <https://github.com/andredezzy/deep-directory-tree-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "andredezzy-deep-filesystem-tree-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/andredezzy-deep-filesystem-tree-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/andredezzy-deep-filesystem-tree-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt