# Claude Document Management MCP Server

> Claude Document Management MCP Server — ailecksandr-claude-course-mcp-task. Use this tool when you need to manage documents using natural language commands, enabling efficient reading and editing of documents through AI-powered interactions. It solves problems related to document management, such as organizing and modifying files, by providing a Ruby-based CLI interface that accepts natural language inputs and generates edited documents as outputs. Ideal for use cases where automated document processing and AI-driven workflows are required.

Canonical page: https://skillsregistry.net/skills/ailecksandr-claude-course-mcp-task  
JSON: https://api.skillsregistry.net/v1/skills/ailecksandr-claude-course-mcp-task

## Description

This MCP server enables Claude AI to read and edit documents through natural language, leveraging tools, resources, and prompts for document management in a Ruby-based CLI application.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ow05pb4s3a)
- **Repository:** <https://github.com/ailecksandr/claude-course-mcp-task>

## 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": "ailecksandr-claude-course-mcp-task"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ailecksandr-claude-course-mcp-task` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ailecksandr-claude-course-mcp-task/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