semvec/pypi-packages huggingface dataset:
pypi-demo-mcp 0.1.0
A demonstration MCP server that can be easily installed to Claude Desktop
License: MIT
Requires Python: >=3.10
Keywords: ai, claude, fastmcp, mcp, model-context-protocol

# PyPI Demo MCP

A demonstration Model Context Protocol (MCP) server showcasing basic tool and resource functionality that can be easily installed to Claude Desktop.

## Overview

This project demonstrates how to create a simple MCP server using the FastMCP framework. It includes:

- A basic addition tool that adds two numbers
- A dynamic greeting resource that provides personalized greetings
- **Automatic Claude Desktop integration** - installs directly to your Claude Desktop configuration
- Proper packaging configuration for PyPI distribution

## Features

### Tools

- **sum**: Adds two integers and returns the result

### Resources

- **greeting**: Dynamic resource that generates personalized greetings based on a name parameter

## Quick Installation for Claude Desktop

### Option 1: Automatic Installation (Recommended)

```bash
# Install the package
pip install pypi-demo-mcp

# Automatically configure Claude Desktop
pypi-demo-mcp install
```

### Option 2: Manual Installation

```bash
# Install the package
pip install pypi-demo-mcp

# Run the setup script
python -m pypi_demo_mcp.server install
```

After installation, **restart Claude Desktop** to use the new MCP server!

- **greeting**: Dynamic resource that generates personalized greetings based on a name parameter

## Installation

### From PyPI (when published)

```bash
pip install pypi-demo-mcp
```

### From Source

```bash
git clone <repository-url>
cd pypi_demo_mcp
pip install .
```

### Using uv (recommended)

```bash
uv sync
```

## Usage

### Running the Server

```bash
python main.py
```

### Using the Tools

The server provides the following MCP tools:

#### Addition Tool

```python
# Tool: sum
# Description: Add two numbers
# Parameters: a (int), b (int)
# Returns: int
```

#### Greeting Resource

```python
# Resource: greeting://{name}
# Description: Get a personalized greeting
# Parameters: name (str)
# Returns: str
```

## Development

### Project Structure

```text
pypi_demo_mcp/
├── main.py           # Main MCP server implementation
├── pyproject.toml    # Project configuration
├── README.md         # This file
└── uv.lock          # Lock file for dependencies
```

### Dependencies

- Python >= 3.10
- mcp[cli] >= 1.10.1

### Configuration

The project uses `pyproject.toml` for configuration following modern Python packaging standards.

## Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test your changes
5. Submit a pull request

## License

This project is intended for demonstration purposes.

## About MCP

The Model Context Protocol (MCP) is a protocol for connecting AI models with various tools and resources. This demo showcases basic MCP server functionality using the FastMCP framework.

For more information about MCP, visit: <https://github.com/modelcontextprotocol>
agentbox-py 1.0.2
AgentBox SDK that give agents cloud environments
License: MIT
Requires Python: <4.0,>=3.9

## What is AgentBox?
[AgentBox](https://agentbox.cloud/) is an infrastructure that allows you to run AI-generated code in secure isolated android sandboxes in the cloud.

## Run your first Sandbox

### 1. Install SDK

```
pip install agentbox
```

### 2. Get your AgentBox API key
1. Sign up to AgentBox [here](https://agentbox.cloud).
2. Get your API key [here](https://agentbox.cloud/dashboard?tab=keys).
3. Set environment variable with your API key 

### 3. Execute code with code interpreter inside Sandbox

```py
from agentbox import Sandbox

with Sandbox() as sandbox:
    sandbox.run_code("x = 1")
    execution = sandbox.run_code("x+=1; x")
    print(execution.text)  # outputs 2
```

### 4. Check docs
Visit [AgentBox documentation](https://agentbox.cloud/docs).