semvec/pypi-packages huggingface dataset:
kipu-quantum-hub-mcp 1.2.7
Kipu Quantum Hub MCP Server
Requires Python: >=3.12

## Setup with Claude Desktop

### Option 1: Using uvx (Recommended)
Add this MCP server config to your `claude_desktop_config.json`:

```json
"kipu-quantum-hub-mcp": {
   "command": "uvx",
   "args": ["kipu-quantum-hub-mcp"],
   "env": {
     "KIPU_ACCESS_TOKEN": "<YOUR_PERSONAL_ACCESS_TOKEN>"
   }
}
```

### Option 2: Local Development Setup
1. Clone the repository 
2. Install uv if you don't have it already
3. Run `uv sync` 
4. Add an MCP server config to the `claude_desktop_config.json`:
   ```json
   "kipu-quantum-hub-mcp": {
      "command": "<UV_PATH>",
      "args": [
         "--directory",
          "<PROJECT_PATH>", 
          "run",
          "src/kipu_quantum_hub_mcp/server.py"
      ],
      "env": {
        "KIPU_ACCESS_TOKEN": "<YOUR_PERSONAL_ACCESS_TOKEN>"
      }
    }
   ```
osint-search-engine-pkg 0.1.5
A unified wrapper for search engines like Serper, DuckDuckGo, etc.
Requires Python: >=3.9

# OSINT Search Engine Wrapper

A lightweight, async wrapper around multiple search engine APIs (Serper/Google, DuckDuckGo, Bing). This package provides a unified, opinionated interface for running OSINT text and image searches.

## Features

- **Async-first:** Built on `httpx` and `aiohttp` for high-performance concurrent searching.
- **Multiple Engines:**
  - **Google** (via Serper API)
  - **DuckDuckGo** (No API key required)
  - **Bing** (via Playwright/Headless Browser)
- **Standardized Results:** Returns clean, consistent JSON-like dictionaries across all engines.

## Installation

Install the package directly from PyPI:

```bash
pip install osint-search-engine-pkg

## Quick start

1. Setup API Keys
For Google (Serper), you need an API key. DuckDuckGo and Bing do not require keys.

```powershell
$env:GOOGLE_SERPER_API_KEY = "your_api_key_here"
```
```Mac/Linux
export GOOGLE_SERPER_API_KEY="your_serper_api_key"
```

2. Usage Example
Here is how to search using all three engines asynchronously:

```python
import asyncio
from search_wrapper import GoogleSearchFromSerper, DuckDuckGoSearch, BingSearch

async def main():
    # --- 1. Google Search (Requires API Key) ---
    # You can pass the key explicitly or rely on the env variable
    async with GoogleSearchFromSerper() as google:
        results = await google.search("OSINT tools python")
        print(f"Google found {len(results.get('data', []))} results")

    # --- 2. DuckDuckGo (No Key Needed) ---
    async with DuckDuckGoSearch() as ddg:
        results = await ddg.search("latest cybersecurity news")
        print(f"DuckDuckGo found {len(results.get('data', []))} results")

    # --- 3. Bing (Headless Browser) ---
    # use headless=False to see the browser action
    async with BingSearch(headless=True) as bing:
        results = await bing.search("site:linkedin.com python developer")
        print(f"Bing found {len(results.get('data', []))} results")

if __name__ == "__main__":
    asyncio.run(main())
```



## Development notes
If you want to contribute or modify the source code:
1. Clone the repository.
2. Install in editable mode:
```bash 
pip install -e
```
3. Run tests using pytest (if available) or run the example scripts in tests/.



## Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

---
ZIPAR 0.1.3
Zip IPA Reconstructor. It generate an IPA package from an installed app on an iOS jailbroken device using Frida.
Requires Python: >=3.10

# ZIPAR

The Zip IPA Reconstructor (or Zip IPA Retriever, if you prefer).

This project re-creates an IPA from an installed Application in an jailbroken iOS device.

This project started as a fork of the famous [**frida-ios-dump**](https://github.com/AloneMonkey/frida-ios-dump)

> The name ZIPAR came as it is an foreignism in portuguese language, that literally means "to zip".

## Installation

To use this tool, it is **highly recomended** to use an virtualenv (although not necessary).
A quick bootstrap:

- `python3 -m venv venv` (the last parameter can be any name to a folder to be venv)
- `source venv/bin/activate`

After that, just install using pip:

`pip install zipar`

Another option is to clone this repo, and to install via **pip**, or run via **uv**.

- `git clone https://github.com/paivao/ZIPAR`
- `pip install .`

## Usage

This tool connects to iOS device using Frida. By default, it uses USB, but can use an remote connection too.

It will attach to the requested application, either by name, bundle id or PID. If name or bundle is used,
but the application is not running, it will be spawned first.

It can, also, attach to the frontmost application.

For more information, use `zipar -h` to get help.

### Issues

If the following error occurs, please open the application before dumping:

* causes device to reboot
* lost connection
* unexpected error while probing dyld of target process

## Contribute

This project uses **uv** to manage, so you need to install it first. It can be installed using `pip` or `cargo`.

The Frida scripts need to be compiled using `frida-compile`, and the package `frida-tools` is needed to run it.

If you modify any *Typescript* code, you need to run `npm run build` inside *agent* directory.