# Filesystem

> Use this tool when you need to interact with the host system's files and directories, enabling tasks such as file management, code analysis, and content generation. It provides a standardized interface for navigation, reading, writing, and analyzing files, with inputs including file paths and metadata, and outputs including file contents and analysis results. Ideal for AI-assisted tasks, it offers batch operations for efficient file manipulation and integration with local filesystem operations.

Canonical page: https://skillsregistry.net/skills/kvas-it-file-system  
JSON: https://api.skillsregistry.net/v1/skills/kvas-it-file-system

## Description

This MCP server implements a comprehensive set of filesystem operations, enabling AI agents to interact with the host system's files and directories. Developed using Python and the FastMCP framework, it provides tools for navigation, reading, writing, and analyzing files, as well as a notes system for metadata. The implementation focuses on offering a wide range of file manipulation capabilities through a standardized interface, including batch operations for improved efficiency. It's particularly useful for AI-assisted file management, code analysis, and content generation tasks, allowing seamless integration of AI capabilities with local filesystem operations.

## 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:** ai-ml
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/kvas-it-file-system)
- **Repository:** <https://github.com/kvas-it/mcp-server-fs>

## 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": "kvas-it-file-system"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kvas-it-file-system` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kvas-it-file-system/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