open-index/open-npm huggingface dataset:
npm package: @jkumonpm/chat-companion-mcp
Description: AI Chat Companion MCP server — natural conversation with Gemini AI (free tier)
Latest version: 1.0.2

# @jkumonpm/chat-companion-mcp

AI Chat Companion MCP server. Natural conversation with Gemini AI (free tier).

No complex prompts. Just talk.

## Install

```bash
npm install -g @jkumonpm/chat-companion-mcp
```

## Usage

### Claude Desktop / Cursor / OpenCode

Add to your MCP config:

```json
{
  "mcpServers": {
    "chat": {
      "command": "npx",
      "args": ["-y", "@jkumonpm/chat-companion-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}
```

> **Note:** You need a Google Gemini API key. Get one for free at [Google AI Studio](https://aistudio.google.com/).

## Tools

### `chat` — Chat with AI Companion

Have a natural conversation with an AI companion. Pass the previous session ID to maintain context.

**Input:**
```json
{
  "message": "你好，今天過得如何？",
  "session": "optional-session-id-from-previous-response"
}
```

**Output:**
```json
{
  "reply": "你好！我今天過得很不錯，謝謝你的問候。那你呢？今天過得還順利嗎？",
  "session": "c6f2f121-bb24-4922-86b8-ed95bb17dbe8"
}
```

### How Session Memory Works

1. **First message:** Don't pass `session`. AI creates a new conversation.
2. **Continue conversation:** Pass the `session` ID from the previous response.
3. **Start fresh:** Don't pass `session` to begin a new conversation.
4. **Auto-cleanup:** Sessions expire after 5 minutes of inactivity.

## Design

| Feature | Why |
|---------|-----|
| Free tier model | Uses `gemini-3-flash-preview` — no cost for users |
| No complex prompts | AI decides how to respond naturally |
| Session memory | Sliding window (last 20 messages) for context |
| Auto-cleanup | Expired sessions cleared every 60 seconds |
| Multi-language | Automatically responds in user's language |

## License

MIT
npm package: @jkumonpm/markdown-utils-mcp
Description: Markdown Utils MCP server — convert to HTML, extract headings/links, word count
Latest version: 1.0.2

# markdown-utils-mcp

Markdown Utils MCP server. Convert to HTML, extract headings/links, word count.

No external dependencies. Pure Regex processing.

## Install

```bash
npm install -g markdown-utils-mcp
```

## Usage

### Claude Desktop / Cursor / OpenCode

Add to your MCP config:

```json
{
  "mcpServers": {
    "markdown-utils": {
      "command": "npx",
      "args": ["-y", "markdown-utils-mcp"]
    }
  }
}
```

## Tools

### `to_html` — Markdown to HTML

Convert Markdown text to HTML.

**Input:**
```json
{
  "markdown": "# Hello\n\nThis is **bold** and *italic*.\n\n[Link](https://example.com)"
}
```

**Output:**
```html
<h1>Hello</h1>
<p>This is <strong>bold</strong> and <em>italic</em>.</p>
<p><a href="https://example.com">Link</a></p>
```

### `extract_headings` — Extract Headings

Extract all headings (H1-H6) from Markdown text.

**Input:**
```json
{
  "markdown": "# Title\n## Section\n### Subsection"
}
```

**Output:**
```json
{
  "count": 3,
  "headings": [
    { "level": 1, "text": "Title" },
    { "level": 2, "text": "Section" },
    { "level": 3, "text": "Subsection" }
  ]
}
```

### `extract_links` — Extract Links

Extract all links from Markdown text.

**Input:**
```json
{
  "markdown": "[Google](https://google.com)\n[GitHub](https://github.com)"
}
```

**Output:**
```json
{
  "count": 2,
  "links": [
    { "text": "Google", "url": "https://google.com" },
    { "text": "GitHub", "url": "https://github.com" }
  ]
}
```

### `word_count` — Word Count

Count words, characters, paragraphs, and lines in Markdown text.

**Input:**
```json
{
  "markdown": "# Hello World\n\nThis is a paragraph with some words."
}
```

**Output:**
```json
{
  "words": 9,
  "characters": 55,
  "charactersNoSpaces": 46,
  "paragraphs": 2,
  "lines": 2
}
```

## Supported Markdown Syntax

| Syntax | Description |
|--------|-------------|
| `# H1` - `###### H6` | Headings |
| `**bold**` | Bold text |
| `*italic*` | Italic text |
| `[text](url)` | Links |
| `` `code` `` | Inline code |
| ` ```lang\ncode\n``` ` | Code blocks |
| `---` | Horizontal rules |
| `> quote` | Blockquotes |
| `- item` | Unordered lists |
| `1. item` | Ordered lists |

## Design

| Feature | Why |
|---------|-----|
| Zero runtime deps | Only `@modelcontextprotocol/sdk` and `zod` |
| Pure Regex | No Markdown parsing library needed |
| Fast conversion | Simple pattern matching, no AST |
| Structured output | JSON in → JSON/HTML out |

## License

MIT
npm package: @jkumonpm/vision-mcp
Description: AI Vision MCP server — analyze images with Gemini AI (free tier)
Latest version: 1.0.2

# @jkumonpm/vision-mcp

AI Vision MCP server. Analyze images, extract text (OCR), and detect objects using Gemini AI.

Free tier model: `gemini-3-flash-preview`.

## Install

```bash
npm install -g @jkumonpm/vision-mcp
```

## Usage

### Claude Desktop / Cursor / OpenCode

Add to your MCP config:

```json
{
  "mcpServers": {
    "vision": {
      "command": "npx",
      "args": ["-y", "@jkumonpm/vision-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}
```

> **Note:** You need a Google Gemini API key. Get one for free at [Google AI Studio](https://aistudio.google.com/).

## Tools

### `analyze_image` — Analyze Image

Analyze one or more images with detailed AI description (objects, environment, colors, mood, etc.).

**Input:**
```json
{
  "image_paths": ["path/to/image.jpg"],
  "prompt": "Optional custom prompt (uses detailed analysis by default)"
}
```

**Output:**
```text
這張圖片是一個典型的終端使用者介面（TUI）截圖...
1. 物體識別：軟體介面元件、標題、方法選擇區...
2. 環境描述：純黑色背景、開發者環境...
...
```

### `extract_text` — Extract Text (OCR)

Extract all text from an image using OCR.

**Input:**
```json
{
  "image_path": "path/to/image.jpg"
}
```

**Output:**
```text
APIReq
Method: GET POST PUT DELETE PATCH
URL: > https://
Headers: | Content-Type: application/json
...
```

### `detect_objects` — Detect Objects

Detect and list all recognizable objects in an image.

**Input:**
```json
{
  "image_path": "path/to/image.jpg"
}
```

**Output:**
```text
- 電腦螢幕：顯示 APIReq 介面
- 游標：白色矩形塊狀游標
- 文字：APIReq, Method, URL, Headers, Body
...
```

## Supported Image Formats

- JPEG / JPG
- PNG
- GIF
- WebP
- BMP
- SVG
- TIFF

**Max file size:** 15MB per image.
**Max images:** 5 per request.

## Design

| Feature | Why |
|---------|-----|
| Free tier model | Uses `gemini-3-flash-preview` — no cost for users |
| Environment variable | API key via `GEMINI_API_KEY` or `GOOGLE_API_KEY` |
| Inline data | Images sent as base64, no upload needed |
| File size check | Rejects files >15MB to avoid API errors |
| Structured prompts | Detailed analysis, OCR, and object detection prompts |

## License

MIT
npm package: @jkun/contextmenu
Description: ## 安装
Latest version: 1.0.1

# yakContextmenu 鼠标右键菜单

## 安装

```bash
npm i @ivy/contextmenu
```

## 使用

```js
import {
  createApp
} from "vue";
import App from "./App.vue";
import Contextmenu from "contextmenu";
import "contextmenu/dist/index.css";

createApp(App).use(Contextmenu).mount("#app");
```

## Attr 和 event

| 属性名        | 说明                                                   | 类型   | 默认值 |
| ------------- | ------------------------------------------------------ | ------ | ------ |
| options         | 配置菜单的数组。例子:[{command: 'copy', text: '复制'}] | Array  | []     |
| menuWrapClass | 菜单容器的类名。                                       | String | -      |
| menuItemClass | 菜单子项的类名。                                       | String | -      |
| menu-click    | 点击菜单时触发的事件，默认参数是一个 Object。          | -      | -      |
| width    | 设置菜单的宽度          | String/Number      | 200px     |
| container    | 菜单生效的元素          | HTMLElement | 合法的css选择器      | document.body      |
npm package: @jkun/create-vue
Description: 生成vue项目模板
Author: GuoJiKun
Latest version: 1.0.0-beta.6

# vue 项目模板生成器

本项目是一个vue模板项目生成器，主要有三个模板

1. 使用 `npm create vue`生成的 `vue3` 项目模板
2. 使用 `@vue/cli` 生成的 `vue3` 项目模板
3. 使用 `@vue/cli` 生成的 `vue2` 项目模板

模板主要功能有：

- `axios` 的二次封装
- 一些工具函数
- `env` 环境的配置
- `.prettierrc`配置文件的统一
- 路由的一些统一处理