# JMComic

> Use this tool when you need to manage and download manga collections efficiently, as it solves problems related to searching, organizing, and accessing manga content through natural language commands. JMComic takes input in the form of user commands and outputs downloaded manga files, with options for PDF generation and file compression. It is ideal for use in contexts where users require streamlined manga collection management and automated downloading capabilities.

Canonical page: https://skillsregistry.net/skills/hect0x7-jmcomic  
JSON: https://api.skillsregistry.net/v1/skills/hect0x7-jmcomic

## Description

JMComic provides MCP server integration for the JMComic-Crawler-Python library, enabling manga searching, downloading, and collection management through natural language commands. The implementation includes tools for album searching, batch downloading, configuration management, and ranking tracking, with built-in support for proxies, authentication, and advanced download options like PDF generation and file compression.

## Trust

- **Trust score (0–1):** 0.51
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/hect0x7-jmcomic)
- **Repository:** <https://github.com/hect0x7/jmcomic-ai>

## 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": "hect0x7-jmcomic"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/hect0x7-jmcomic` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/hect0x7-jmcomic/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