# File System MCP Server

> Use this tool when you need to automate file system operations using natural language commands, solving problems such as file management and data organization. It takes in natural language inputs and outputs automated file system actions, utilizing a Python bridge agent and LLM technology. This tool is ideal for streamlining file management tasks and improving productivity in various contexts, including data analysis and software development.

Canonical page: https://skillsregistry.net/skills/terzeron-mcp-test  
JSON: https://api.skillsregistry.net/v1/skills/terzeron-mcp-test

## Description

Automates file system operations through natural language commands using a combination of LLM (Ollama), MCP tools, and a Python bridge agent.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/r7forfi2tj)
- **Repository:** <https://github.com/terzeron/mcp_test>

## 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": "terzeron-mcp-test"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/terzeron-mcp-test` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/terzeron-mcp-test/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