semvec/pypi-packages huggingface dataset:
undetected 0.0.12
Selenium.webdriver.Chrome replacement with compatibility for Brave, and other Chromium based browsers. Not triggered by CloudFlare/Imperva/hCaptcha and such. NOTE: results may vary due to many factors. No guarantees are given, except for ongoing efforts in understanding detection algorithms.
Requires Python: <4,>=3.10

# Undetected

![PyPI - Version](https://img.shields.io/pypi/v/undetected) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/undetected) ![License](https://img.shields.io/pypi/l/undetected) ![Downloads](https://img.shields.io/pypi/dm/undetected)

Undetectable selenium chromedriver.

**Note:** This project is a fork of [`undetected-chromedriver`](https://github.com/ultrafunkamsterdam/undetected-chromedriver).

## Installation

```bash
pip install undetected
````

## Simple Usage

```python
import undetected as uc

driver = uc.Chrome()
driver.get("https://example.com")
driver.quit()
```

## Example Usage with Multiprocessing

```python
import undetected as uc
from undetected.patcher import Patcher
import multiprocessing as mp

def worker(idx: int):
    driver = uc.Chrome(user_multi_procs=True)
    driver.get("https://example.com")
    driver.quit()

if __name__ == "__main__":
    Patcher.patch()  # patching a unique undetected chromedriver

    processes = [mp.Process(target=worker, args=(i,)) for i in range(4)]
    for p in processes:
        p.start()
    for p in processes:
        p.join()
```
lifx-emulator 4.3.0
Standalone LIFX Emulator with CLI and HTTP management API
Requires Python: >=3.10

# lifx-emulator

Standalone LIFX device emulator with CLI and HTTP management API.

This package provides a ready-to-run emulator for testing LIFX LAN protocol libraries. It includes a command-line interface and an optional HTTP API for runtime device management.

## Installation

```bash
pip install lifx-emulator
```

## Quick Start

```bash
# Start with default configuration (1 color light)
lifx-emulator

# Create multiple device types
lifx-emulator --color 2 --multizone 1 --tile 1

# Enable HTTP management API
lifx-emulator --api

# List available LIFX products
lifx-emulator list-products

# Create devices by product ID
lifx-emulator --product 27 --product 38 --product 55
```

## Features

- Command-line interface for quick emulator setup
- HTTP management API with web dashboard
- Real-time device monitoring and management
- Support for all LIFX device types (color, multizone, tile, infrared, HEV, switch)
- Persistent device state across restarts
- Testing scenarios for protocol edge cases

## HTTP Management API

Enable with `--api` to get:

- **Web Dashboard**: `http://localhost:8080` - Real-time monitoring UI
- **REST API**: Device management, statistics, and scenario control
- **OpenAPI Docs**: `http://localhost:8080/docs` - Interactive API documentation

```bash
# Start with API server
lifx-emulator --color 2 --api --api-port 9090

# Add a device via API
curl -X POST http://localhost:9090/api/devices \
  -H "Content-Type: application/json" \
  -d '{"product_id": 27}'
```

## Documentation

Full documentation is available at: **https://djelibeybi.github.io/lifx-emulator**

- [Installation Guide](https://djelibeybi.github.io/lifx-emulator/getting-started/installation/)
- [CLI Reference](https://djelibeybi.github.io/lifx-emulator/cli/cli-reference/)
- [Web Interface](https://djelibeybi.github.io/lifx-emulator/cli/web-interface/)
- [REST API](https://djelibeybi.github.io/lifx-emulator/cli/device-management-api/)

## Related Packages

- **[lifx-emulator-core](https://pypi.org/project/lifx-emulator-core/)**: Core library for embedding the emulator in your own projects

## License

[UPL-1.0](https://opensource.org/licenses/UPL)
iflow-mcp_s1lv3rj1nx_mcp-demo 0.1.3
Add your description here
Requires Python: <3.13,>=3.12

# Model Context Protocol (MCP)

The Model Context Protocol (MCP) is a powerful framework that enables developers to build AI applications with large language models (LLMs) by providing a standardized way to connect models with external data sources and tools.

MCP is nothing but a protocol to connect LLMs with external data sources and tools (functions).

## MCP Server

This repository contains the code for setting up a demo MCP server. It contains:

- A stateless MCP server with streamable HTTP transport for scalable production deployment.
- Auto tool registry with `@mcp_tool` decorator.
- Docker file to containerize the server.
- Server can be run locally or in docker and deployed to any cloud provider.

## Setup

- Install uv

```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```

- Install dependencies

```bash
uv sync
```

## MCP Client

This repository contains the code for setting up a demo MCP client with OpenAI SDK. Refer to the [client](client/README.md) for more details.

> Note: For ease of understanding, both server and client are in the same repository, you can easily keep them in separate repositories / projects.