# Filesystem

> Use this tool when you need to securely interact with local filesystem resources from LLM applications, enabling controlled access to files and directories for browsing, reading, writing, and manipulation. It solves problems related to secure file access and manipulation, handling various file types and large files while maintaining security boundaries. Ideal for AI applications that require local file interaction, this tool provides a robust interface for secure filesystem operations.

Canonical page: https://skillsregistry.net/skills/qiangmzsx-filesystem  
JSON: https://api.skillsregistry.net/v1/skills/qiangmzsx-filesystem

## Description

A Go implementation of the Model Context Protocol (MCP) that enables seamless integration between LLM applications and local filesystem resources. This server provides secure, controlled access to files and directories through a set of tools for browsing, reading, writing, and manipulating filesystem content. It features robust path validation to prevent unauthorized access, supports various file types including text and images, and handles large files appropriately through resource references. Built as a learning project based on the mark3labs implementation, it's useful for AI applications that need to interact with local files while maintaining security boundaries.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/qiangmzsx-filesystem)
- **Repository:** <https://github.com/qiangmzsx/mcp-filesystem-server>

## 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": "qiangmzsx-filesystem"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/qiangmzsx-filesystem` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/qiangmzsx-filesystem/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