open-index/open-npm huggingface dataset:
npm package: @itaykarkason/mcp-vibe
Description: A fun MCP server that generates daily vibes using free APIs
Latest version: 0.1.0

# 🌈 Daily Vibe Generator - MCP Server

**עוזר שנותן לך "וייב יומי" אמיתי — מבוסס על APIs חינמיים**

MCP server חמוד וקליל שנותן לך וייב יומי עם ציטוטים, עובדות מעניינות, ועצות מותאמות אישית לפי השעה והיום.

## ✨ מה זה עושה?

כלי אחד פשוט: `get_daily_vibe()`

ה-MCP:
1. 🎯 מושך **ציטוט אקראי** מ-API חינמי
2. 🐱 מושך **עובדה אקראית / חיה חמודה / בדיחה**
3. ⏰ משלב את זה עם השעה והיום
4. 💫 מחזיר "וייב" קצר וחמוד עם עצה מותאמת

## 🚀 התקנה

```bash
# דרישות: Node.js 18+ ו-npm

# התקנת תלויות
npm install

# בניית הפרויקט
npm run build
```

## 📦 APIs חינמיים (בלי מפתח!)

השרת משתמש ב-APIs חינמיים לחלוטין:

- **Quotable** - ציטוטים יפים: `https://api.quotable.io/random`
- **Cat Facts** - עובדות על חתולים: `https://catfact.ninja/fact`
- **Numbers API** - עובדות מוזרות על מספרים: `http://numbersapi.com/random/trivia?json`
- **Joke API** - בדיחות: `https://official-joke-api.appspot.com/random_joke`

## 🎯 שימוש

### כשרת MCP

הוסף את השרת ל-Cursor/Claude Desktop:

```json
{
  "mcpServers": {
    "daily-vibe": {
      "command": "node",
      "args": ["/path/to/mcp-vibe/dist/server.js"]
    }
  }
}
```

או עם `tsx` לפיתוח (ללא build):

```json
{
  "mcpServers": {
    "daily-vibe": {
      "command": "npx",
      "args": ["tsx", "/path/to/mcp-vibe/server.ts"]
    }
  }
}
```

### כסקריפט עצמאי

```bash
# לאחר build
npm start

# או עם tsx (ללא build)
npm run dev
```

## 📝 דוגמה לתוצאה

```json
{
  "vibe": "🌅 בוקר - מוטיבציה ופוקוס | יום ראשון - התחלה חדשה",
  "quote": "Simplicity is the ultimate sophistication.",
  "author": "Leonardo da Vinci",
  "fun_fact": "Cats sleep for around 70% of their lives.",
  "suggestion": "תתחיל את היום עם משהו קטן וקל",
  "timestamp": "2024-01-15 09:30:00"
}
```

## 🎨 תכונות

### ⏰ וייבים מותאמים לפי זמן

- **🌅 בוקר מוקדם (5-9)** - אנרגיה טרייה
- **☀️ בוקר (9-12)** - מוטיבציה ופוקוס
- **🌆 צהריים (12-14)** - אנרגיה גבוהה
- **🌆 אחר הצהריים (14-17)** - יצירתיות
- **🌆 ערב (17-21)** - רוגע וסיכום
- **🌙 לילה (21-5)** - מנוחה והתבוננות

### 📅 התאמה לפי יום בשבוע

- **יום ראשון** - התחלה חדשה
- **יום חמישי** - בוסט לפני סוף השבוע
- **יום שישי** - סוף שבוע מתקרב

## 🛠️ פיתוח

הקוד כתוב ב-TypeScript/Node.js ומשתמש ב:
- `@modelcontextprotocol/sdk` - MCP SDK
- `axios` - HTTP client
- `typescript` - TypeScript compiler
- `tsx` - TypeScript execution (לפיתוח)

### סקריפטים זמינים

```bash
npm run build    # קומפילציה ל-JavaScript
npm start        # הרצת השרת (לאחר build)
npm run dev      # הרצה ישירה עם tsx (ללא build)
```

## 📄 רישיון

MIT License - חופשי לשימוש!

## 🤝 תרומה

תמיד שמחים לתרומות! פתח issue או PR.

---

**נהנה מהוייב היומי שלך! 🌈✨**
npm package: @itaylor/just_my_type
Description: Derives typescript types from JS objects
Author: ian.b.taylor@gmail.com
Latest version: 0.0.6

# just_my_type

*Experimental!!!*

Attempts to infer a typescript type by inspecting runtime javascript objects. 

## Why would I want this?
* You have a large API that is not currently typed
* There are no/poor specifications or documentation of what the shape of the objects it returns
* The responses it return vary, and it's difficult to know that you have a complete understanding of what it can return
* You want to write a type for it

## How to use:
The idea is that you want to run this on a real-world system, observing the real-world data for a while, then after some time has passed and you've observed many responses, you ask it to suggest a type that will match for all of them.

For each object you'd want to generate a type for, you'd create an instance of `TypeGenerator` then call `observe`, passing the data that you're wanting to generate a type for.  After some time has passed and you think you have a complete understanding of what the API does, you'd call `suggest` and it'll make you a `typescript` type that fits the observed data.

## Setup (node.js):
```sh
npm install @itaylor/just-my-type
```
```ts
import TypeGenerator from '@itaylor/just_my_type';
```

## Setup (deno):
```ts
import TypeGenerator from 'https://deno.land/x/just_my_type@0.0.1/main.ts';
```

## Usage
```ts
const tg = new TypeGenerator('MyAPI');

// Assumption: this api is being called by your application somewhere on a regular basis.
export async function myApi() {
  const data = await (await fetch('https://someserver.local/myApiThatINeedATypeFor/')).json();
  tg.observe(data);
  return data;
}
// This is a bad way to do this, but illustrates the point that `observe` should be called multiple times 
// With all the different variations that need to be observed before calling `suggest`
setInterval(() => console.log(tg.suggest()), 5 * 60 * 1000);
```
Every 5 minutes you'd see something like this in the logs that would be the current representation of all the data that has been observed:
```ts
export type MyAPI = {
  startIndex: number,
  maxReturn: number,
  items: Array<{
    type: string,
    children: Array<{
      x: number,
      y: number
    }>
  } | {
    type: string,
    messageText: string
  } | {
    type: string,
    responses: Array<string>
  }>
}
```
npm package: @itaylor/markdowner
Description: Convert various file formats to markdown using AI and specialized converters
Latest version: 0.0.2

# Markdowner

Convert various file formats to markdown using AI and specialized converters.

## Supported Formats

- **PDF** (.pdf) - AI-powered conversion with image analysis
- **Images** (.png, .jpg, .jpeg) - AI vision model describes content
- **Word** (.docx) - Direct conversion
- **PowerPoint** (.pptx) - Extract slides and content
- **Excel** (.xlsx) - Convert to markdown tables
- **Text** (.txt, .md) - Pass-through

## Requirements

**For AI features (choose one):**

**Option 1: OpenAI (or compatible services):**

```bash
# Get API key from OpenAI, or use any OpenAI-compatible service
export OPENAI_API_KEY="your-api-key-here"
```

**Option 2: Ollama (local):**

```bash
# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh

# Pull model and start server
ollama pull gemma3:27b
ollama serve
```

## CLI Usage

```bash
# Convert file to markdown (uses local Ollama by default)
markdowner document.pdf

# Save to file
markdowner document.pdf -o output.md

# Use OpenAI
markdowner document.pdf \
  --openai-base-url https://api.openai.com/v1 \
  --openai-api-key $OPENAI_API_KEY \
  --openai-model gpt-4-vision-preview

# Use Ollama on remote server
markdowner document.pdf \
  --openai-base-url http://remote:11434/v1 \
  --openai-api-key ollama \
  --openai-model gemma3:27b

# Legacy Ollama syntax (still supported)
markdowner file.pdf --ollama-url http://localhost:11434

# Disable AI (faster, basic extraction for pdfs, images will throw)
markdowner document.pdf --no-ai
```

## Library Usage

```javascript
import { markdowner } from 'markdowner';

// With OpenAI
const markdown = await markdowner('./document.pdf', {
  openai: {
    baseURL: 'https://api.openai.com/v1',
    apiKey: process.env.OPENAI_API_KEY,
    model: 'gpt-4-vision-preview',
  },
});

// With Ollama using OpenAI-compatible API
const markdown = await markdowner('./document.pdf', {
  openai: {
    baseURL: 'http://localhost:11434/v1',
    apiKey: 'ollama', // required but unused
    model: 'gemma3:27b',
  },
});

// Legacy Ollama syntax (still supported)
const markdown = await markdowner('./document.pdf', {
  ollamaUrl: 'http://localhost:11434',
});

// Without AI (faster, basic extraction only)
const markdown = await markdowner('./document.pdf', {});
```
npm package: @itaylor/rewire-proxy-runtime
Description: Runtime library for babel-plugin-rewire-proxy
Author: ian.b.taylor@gmail.com
Latest version: 0.0.20

# rewire-proxy-runtime

This is the runtime dependency that is used by [@itaylor/babel-plugin-rewire-proxy](https://github.com/itaylor/rewire-proxy)

Please see the instructions for usage there there.

Distributed under the MIT license.
npm package: @itayzrihan/create-box-app
Description: Create a new BOX Framework application with one command
Author: Itay Zrihan
Latest version: 1.1.0

# create-box-app

> Scaffold a new BOX Framework project in seconds

## Quick Start

```bash
npx create-box-app my-project
cd my-project
npm install
npm run dev
```

That's it! Your BOX app is ready at `http://localhost:3000`

## What's Inside

The scaffolder creates a minimal BOX project with:

- ✅ Pre-configured `.vscode` settings for HTML syntax highlighting
- ✅ Sample `main.box` component demonstrating the framework
- ✅ Example API endpoint (`api+hello.box`)
- ✅ Ready-to-use npm scripts (`dev`, `build`, `start`)
- ✅ Clean folder structure following BOX conventions

## Features

- **Zero Setup**: No global installs. Just `npx` and go.
- **Fast**: Generates a working project in under 5 seconds
- **Minimal**: Only essential files, no bloat
- **Beautiful**: Includes a stylish welcome component

## Commands

Once your project is created:

```bash
npm run dev      # Start dev server with HMR
npm run build    # Build for production
npm start        # Run production server
```

## Learn More

- [BOX Framework Docs](https://github.com/itayzrihan/box)
- [GitHub Repository](https://github.com/itayzrihan/box)

## License

MIT © Itay Zrihan