semvec/pypi-packages huggingface dataset:
overkiz-mcp 0.1.0
MCP server for controlling lights using overkiz
Requires Python: >=3.13.3

# overkiz-mcp MCP server

MCP server for controlling lights using pyoverkiz

## Components

### Resources

The server implements a light control system with:
- Custom light:// URI scheme for accessing individual light devices
- Each light resource has a name and current state (On/Off)
- The resources are automatically discovered from your Overkiz/Somfy account

### Tools

The server implements three tools:
- list-lights: Lists all available lights and their current status
  - Takes no arguments
- light-on: Turns on a light by name
  - Takes "name" as a required string argument
- light-off: Turns off a light by name
  - Takes "name" as a required string argument

## Configuration

The server requires the following environment variables:
- OVERKIZ_USERNAME: Your Overkiz/Somfy account username
- OVERKIZ_PASSWORD: Your Overkiz/Somfy account password
- OVERKIZ_SERVER: The Overkiz server to connect to (defaults to "somfy-europe")

## Quickstart

### Set Environment Variables

Before running the server, make sure to set your Overkiz credentials:

```bash
export OVERKIZ_USERNAME="your-email@example.com"
export OVERKIZ_PASSWORD="your-password"
export OVERKIZ_SERVER="somfy-europe"  # Defaults to somfy-europe if not specified
```

### Install

```bash
pip install overkiz-mcp
```

Or install directly from the repository:

```bash
pip install git+https://github.com/phimage/mcp-overkiz.git
```

### Running with Claude Desktop

#### Claude Desktop

On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

<details>
  <summary>Development/Unpublished Servers Configuration</summary>
  
  ```json
  "mcpServers": {
    "overkiz-mcp": {
      "command": "uv",
      "args": [
        "run",
        "overkiz-mcp"
      ],
      "env": {
        "OVERKIZ_USERNAME": "your-email@example.com",
        "OVERKIZ_PASSWORD": "your-password",
        "OVERKIZ_SERVER": "somfy-europe"
      }
    }
  }
  ```
</details>

<details>
  <summary>Published Servers Configuration</summary>
  
  ```json
  "mcpServers": {
    "overkiz-mcp": {
      "command": "uv",
      "args": [
        "overkiz-mcp"
      ],
      "env": {
        "OVERKIZ_USERNAME": "your-email@example.com",
        "OVERKIZ_PASSWORD": "your-password",
        "OVERKIZ_SERVER": "somfy-europe"
      }
    }
  }
  ```
</details>

### Example Usage

Once the server is running and connected to Claude, you can control your lights with commands like:

- "List all my lights"
- "Turn on the living room light"
- "Turn off the bedroom light"
fidlyai 1.1.1
FidlyAI is a highly effective AI package for Python, designed to be user-friendly.
Requires Python: >=3.6
Keywords: gemini, fidlyai, google gemini, gemini ai, ai wrapper, gemini api, google ai, fidal, mr fidal, python ai, multi-user ai, ask gemini, chat gemini, bulk prompts, gemini python wrapper

# 💬 fidlyai

**fidlyai** is a powerful and flexible Python package for interacting with Google's Gemini 2.0 Flash API. Built to support multiple users, handle bulk prompts, and maintain chat memory per user, it's the perfect AI companion for developers, researchers, and builders.

---

## ✨ Features

- 🔐 Support for multiple API keys (multi-user ready)
- 💬 Chat-like session handling with memory per user
- 📤 Send and process multiple prompts in one go
- ⚡ Fast single-prompt requests
- 📦 Lightweight with zero dependencies except `requests`
- 🧩 Easy integration into any Python project
- 💡 Great for AI chatbots, automation, assistants, and research

---

## 📦 Installation

```bash
pip install fidlyai
```

---

## 💡 Basic Usage

```python
from fidlyai import gemini

api = gemini("YOUR_GEMINI_API_KEY")
response = api.ask("What is Artificial Intelligence?")
print(response)
```

---

## 🔁 Bulk Prompting

Send multiple prompts in a single session:

```python
prompts = ["What is AI?", "Explain Python.", "Uses of the internet."]
answers = api.bulk_ask(prompts)

for ans in answers:
    print(ans)
```

---

## 👥 Chat with User Memory

Each user gets isolated memory context:

```python
user = "user123"
print(api.chat(user, "Hey Gemini, who are you?"))
print(api.chat(user, "What did I just ask you?"))
```

This creates a memory-like flow for each user separately — ideal for chatbots or interactive tools.

---

## 🔑 Authentication

To use fidlyai, you need a Gemini API key:

1. Visit [Google AI Studio](https://aistudio.google.com/app/apikey)
2. Create a project
3. Get your Gemini 2.0 Flash API key
4. Use it like: `gemini("YOUR_KEY")`

---

## 🧪 Use Cases

- AI-powered chat systems
- Educational tools
- Creative writing assistants
- Code generators
- Research projects
- Interactive Q&A bots
- Multi-user systems with context retention

---

## 🧑‍💻 Author

Developed with ❤️ by [Fidal PalamParambil (mr-fidal)](https://github.com/mr-fidal)  
Email: `mrfidal@proton.me`

---

## 📃 License

MIT License © 2025 Fidal

---