semvec/pypi-packages huggingface dataset:
videodb-director-mcp 0.1.7
VideoDB MCP Server
Requires Python: >=3.12

[![smithery badge](https://smithery.ai/badge/@video-db/agent-toolkit)](https://smithery.ai/server/@video-db/agent-toolkit)

To add the MCP server in any config driven MCP Client, following is how the commands and arguments will look like

## Install `uv`
We need to install uv first.

For macOS/Linux:
```
curl -LsSf https://astral.sh/uv/install.sh | sh
```
For Windows:

```
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
```

You can also visit the installation steps of `uv` for more details [here](https://docs.astral.sh/uv/getting-started/installation)

## Run the MCP Server
You can run the MCP server using `uvx` using the following command

```
uvx videodb-director-mcp --api-key=VIDEODB_API_KEY
```

## Add the VideoDB Director MCP Server in your favorite Client

### Claude Desktop

To configure VideoDB Director MCP server in Claude, you can run the following command

```uvx videodb-director-mcp --install=claude```

You can manually configure the MCP Server by following these steps:

1. Open the `claude_desktop_config.json` file

   In MacOS/Linux:

   ```
   code ~/Library/Application\ Support/Claude/claude_desktop_config.json
   ```

   In Windows:

   ```
   code $env:AppData\Claude\claude_desktop_config.json
   ```

2. Add the VideoDB Director MCP Server inside the `mcpServers` key:

   ```json
   {
     "mcpServers": {
       "videodb-director": {
         "command": "uvx",
         "args": ["videodb-director-mcp", "--api-key=<VIDEODB-API-KEY>"]
       }
     }
   }
   ```

### Cursor

To configure VideoDB Director MCP server in Cursor, you can run the following command

```uvx videodb-director-mcp --install=cursor```

You can manually configure the MCP Server by following these steps:

1. Inside Cursor, go to **Settings > Cursor Settings**
2. Click on **MCP**
3. Click on **Add new Global MCP Server**
4. Add the VideoDB Director MCP Server under the `mcpServers` key

   ```json
   {
     "mcpServers": {
       "videodb-director": {
         "command": "uvx",
         "args": ["videodb-director-mcp", "--api-key=<VIDEODB-API-KEY>"]
       }
     }
   }
   ```

### Install in Claude and Cursor at the same time.
You can configure VideoDB Director MCP server in Claude and Cursor together, by running the following command

```
uvx videodb-director-mcp --install=all
```


### Install for Claude Code

```
claude mcp add videodb-director uvx -- videodb-director-mcp --api-key=<VIDEODB_API_KEY>
```

## Update VideoDB Director MCP package

To ensure you're using the latest version of the MCP server with `uvx`, start by clearing the cache:

```
uv cache clean
```

This command removes any outdated cached packages of `videodb-director-mcp`, allowing `uvx` to fetch the most recent version.

If you always want to use the latest version of the MCP server, update your command as follows:
```
uvx videodb-director-mcp@latest --api-key=<VIDEODB_API_KEY>
```
funtypes 0.2.1
FUNctional types for Python. (Backport to 0.2.1)
Requires Python: <4.0,>=3.12

# fntypes

Functional typing in Python!

See [examples](/examples/)

See [documentation](/docs/index.md)

fntypes is based on the belief that raising exceptions **should be avoided**. Therefore, it offers a set of functional types needed to write better code. This type strategy grants your project with higher control over type system - improves control flow

Contributions are welcome


```python
@unwrapping
def send_funds(
    sender_id: int, 
    receiver_id: int, 
    amount: decimal.Decimal,
) -> Result[TransactionID, str]:
    sender = get_user(sender_id).expect("Sender is undefined")
    receiver = get_user(receiver_id).expect("Receiver is undefined")
    if sender.get_balance().unwrap() < amount:
        return Error("Sender has not enough funds to complete transaction")
    
    return Ok(
        create_transaction(sender, receiver, amount)
        .unwrap()
        .transaction_id
    )
```
llmscraper 0.1.0
LLM-powered web scraping in Python
Requires Python: >=3.9

# LLM Scraper Python

A Python port of the [LLM-powered web scraping library](https://github.com/mishushakov/llm-scraper), using `html2text` for HTML processing.

## Installation

1.  **Create a virtual environment and install dependencies:**
    ```bash
    uv sync
    ```
2.  **Install Playwright browser binaries:**
    ```bash
    uv run playwright install
    ```

## Usage
```python
import asyncio
from typing import List
from playwright.async_api import async_playwright
from pydantic import BaseModel
from openai import AsyncOpenAI
from llmscraper import LLMScraper

class Story(BaseModel):
    title: str
    url: str
    points: int
    by: str
    comments: int

class HackerNews(BaseModel):
    stories: List[Story]

async def main():
    client = AsyncOpenAI()
    scraper = LLMScraper(client)

    async with async_playwright() as p:
        browser = await p.chromium.launch()
        page = await browser.new_page()
        await page.goto("https://news.ycombinator.com")

        result = await scraper.run(
            page,
            schema=HackerNews,
            options={"limit": 5},
        )
        print(result)

        await browser.close()

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

## Examples

See the `examples/` directory for more usage examples.
nuvolos-cli 1.1.1
Command-line interface for Nuvolos
Requires Python: >=3.8

<!-- [![PyPI version](https://img.shields.io/pypi/v/nuvolos-cli)](https://pypi.org/project/nuvolos-cli/)  -->
[![Docs](https://readthedocs.org/projects/nuvolos-cli/badge/)](https://nuvolos-cli.readthedocs.io/en/latest/)
<!-- [![Integration tests](https://github.com/nuvolos-cloud/nuvolos-cli/actions/workflows/integration-test.yaml/badge.svg)](https://github.com/nuvolos-cloud/nuvolos-cli/actions/workflows/integration-test.yaml) -->


```
 _   _                  _              ____ _     ___ 
| \ | |_   ___   _____ | | ___  ___   / ___| |   |_ _|
|  \| | | | \ \ / / _ \| |/ _ \/ __| | |   | |    | | 
| |\  | |_| |\ V / (_) | | (_) \__ \ | |___| |___ | | 
|_| \_|\__,_| \_/ \___/|_|\___/|___/  \____|_____|___|
                                                      
```

Nuvolos CLI is command-line interface (CLI) for the [Nuvolos](https://nuvolos.cloud) platform. It allows you to interact with the Nuvolos platform from your local terminal.

It interacts with the [Nuvolos REST API](https://api.nuvolos.cloud/docs) via the [nuvolos-client-api](https://github.com/nuvolos-cloud/nuvolos-client-api) package.

For installation and detailed usage, check out the [documentation](https://nuvolos-cli.readthedocs.io/en/latest/).

## Installation

You can install the latest stable version using pip with

```
pip install nuvolos-cli
```