semvec/pypi-packages huggingface dataset:
pycapabilitydecorator 0.0.3
Python capability decorator for creating modular applications
License: MIT
Requires Python: >=3.8


# PyCapabilityDecorator 说明文档
能力插件,将普通代码转换为能力插件

支持：
    1. 定义 capability 元数据，包括初始化参数描述 (init_params) 和语言类型 (language_type)。
    2. 注册顶级 CLI 命令（@option），支持可选的 alias，name 默认为函数名。
    3. 添加顶级 --capability 选项输出所有 capability 元数据。
    4. 添加顶级 init 命令执行初始化。
    5. init_params 元数据描述初始化参数。
    6. server(命令)      运行服务器 服务自动注册 pages 和 methods
        页面模板路径  assets/pages
        静态资源路径  assets/static

        访问页面:
            http://127.0.0.1:5000/capability/<>/pages/<>
        运行方法:
            http://127.0.0.1:5000/capability/<>/methods/<>



生命周期:
    1.register(命令)    注册 capability 元数据
    2.init(命令)        初始化
    3.start(命令)       启动能力
    4.stop(命令)        停止能力
    5.destroy(命令)     销毁能力


gitee:
https://gitee.com/iiixxxiii/py-capability-decorator.git





## 使用




### 安装
``` bash
pip install pycapabilitydecorator
```



### 示例

最简单的用法

```python
# simple.py
from pycapabilitydecorator  import capability

# ---- 最简单能力接入
@capability.option()
def function1():
    return {
        "code": 0,
        "message": "[function1]成功"
    }
```

启动

```bash
python simple.py  server
```

执行方法
参数m 或者 method

```bash
curl http://127.0.0.1:5000/methods/simple/function1
```

访问页面
```bash
curl http://127.0.0.1:5000/pages/simple/home.html
```

## 项目编译


```bash

# 构建
uv build



# 测试安装1
pip install dist/pycapabilitydecorator-0.0.1-py3-none-any.whl


# 测试安装2
pip install -e


# 运行示例文件

cd examples/simple

python capability_simple.py server


# 安装 twine
pip install twine

# 上传到 PyPI

python -m twine upload dist/*


pippy地址:
https://pypi.org/project/pycapabilitydecorator/

```
mcp-fileparser 0.1.3
A file parser using Kimi AI
License: MIT
Requires Python: >=3.9
Keywords: mcp, fileparser

# MCP File Parser

[![PyPI version](https://badge.fury.io/py/mcp-fileparser.svg)](https://badge.fury.io/py/mcp-fileparser)

A file parser using Kimi AI. However, all of this is free.

## Installation

```bash
pip install mcp-fileparser
```

## Usage

### As a Python Library

1.  **Set up your environment variables.**

    Create a `.env` file in your project root and add your Kimi API key:

    ```
    KIMI_API_KEY="your_api_key"
    ```

2.  **Use the `parse_file` function.**

    ```python
    from mcp_fileparser import parse_file

    content = parse_file("/path/to/your/file.xlsx")
    print(content)
    ```

### As an MCP Server

This package can also be used as an MCP (Model Context Protocol) server, providing file parsing capabilities to MCP clients.

#### Installation

1.  **Install the package:**

    ```bash
    pip install mcp-fileparser
    ```

2.  **Set up your environment variables:**

    Create a `.env` file in your project root and add your Kimi API key:

    ```
    KIMI_API_KEY="your_api_key"
    ```

#### Configuration

Add the MCP server to your MCP client configuration. For example, in Claude Desktop or other MCP-compatible clients:

```json
{
  "mcpServers": {
    "mcp-fileparser": {
      "command": "npx",
      "args": [
        "--from",
        "mcp-fileparser",
        "parse_file"
      ],
      "env": {
        "KIMI_API_KEY": "your_api_key"
      }
    }
  }
}
```

#### Available Tools

Once connected, the MCP server provides the following tool:

- **`parse_file`**: Parse a file and extract its content using Kimi AI
  - **Parameters**: 
    - `fpath` (string): The path to the file you want to parse
  - **Returns**: The extracted content as a string

#### Example Usage

In an MCP-compatible client, you can use the `parse_file` tool like this:

```python
# Example of how the tool would be called by an MCP client
result = await client.call_tool("parse_file", {
  "fpath": "/path/to/your/document.pdf"
})
print(result.content)
```

#### Supported File Types

The file parser supports various file types including:
- PDF documents
- Word documents (.docx)
- Excel spreadsheets (.xlsx)
- Text files (.txt)
- And many other formats supported by Kimi AI

#### Running the Server Manually

You can also run the MCP server manually for testing:

```bash
# Set your API key
export KIMI_API_KEY="your_api_key"

# Run the server
fileparser
```

The server will start and listen for MCP connections via stdio transport.

## License

This project is licensed under the MIT License.