semvec/pypi-packages huggingface dataset:
pyads-ipc-diag 0.2.0
Read Beckhoff IPC Diagnostics via ADS using pyads
License: MIT
Requires Python: >=3.9

# Beckhoff IPC Diagnostics

**pyads-ipc-diag** is a Python library for reading IPC Diagnostics information from Beckhoff IPCs and EPCs.

IPC Diagnostics have been available on Beckhoff IPC/EPC devices for years. The data can be accessed via ADS, OPC UA, or C#.  
This library focuses on **ADS access using Python**.

For detailed documentation, see the Beckhoff Information System:  
https://infosys.beckhoff.com/content/1033/devicemanager/index.html?id=7887654213086576625

The library uses [**pyads**](https://github.com/stlehmann/pyads) for ADS communication. pyads is supported on multiple platforms, including Windows, Linux, and FreeBSD.

**This project is still under development and may be unstable.**

Documentation is also under preparation!

---

## Installation

### Install using pip (recommended)

```bash
pip install pyads-ipc-diag
```

### Clone from source

```bash
git clone https://github.com/dewabe/pyads-ipc-diag.git
cd pyads-ipc-diag
pip install -e .
```

---

## Features

- Read all IPC Diagnostics data via ADS - just check the documentation provided by Beckhoff
- Available modules to read: CPU, Fan, Mainboard, Memory, NIC, OS, Software, Time, TwinCAT, UserManagement

### Command Line Arguments
You can also use command line arguments, in example store all the data into file output.json:
```bash
pyads-ipc-diag --ams-net-id 1.2.3.4.1.1 --module all --json output.json
```

For more information, use

```bash
pyads-ipc-diag -h
```

---

## Basic usage

```python
import pyads
from pyads_ipc_diag import MDP, CPU, CONFIG_AREA

with MDP("10.10.10.11.1.1") as ipc:
    cpu = CPU(ipc)
    print(cpu.properties())
    # CPU_Info(
    #   frequency=1917,
    #   usage=3,
    #   temperature=43
    #   )
    mac_address = ipc.read(CONFIG_AREA.NIC, 0x8001, 1, pyads.PLCTYPE_STRING)
    print(mac_address) # nn:nn:nn:nn:nn:nn
```

---

## Requirements

- Python 3.9+
- pyads
- Beckhoff IPC/EPC with IPC Diagnostics available


## To Do

* All "High level MDP Service Classes", such a Memory, NIC, UPS etc.
* Possibility to write data (i.e. change IP address)
* Optimize code
* Write tests
* Write documentation
skills-for-all-agent 0.1.1
Lightweight skill loader and runner for agent function calling.
License: MIT
Requires Python: >=3.8
Keywords: agent, skills, tooling, function-calling

# Skills-For-All-Agent-首个无缝支持所有agent框架的skill系统

与**Claude Code**的skills system完全吻合的实现-同时不仅仅局限于**Claude Code的skills system，它 更轻量化 更兼容 更自由化 更生态化**

## 这是什么

一个python package 作为skills系统去无缝接轨所有agent框架，并将skill内容和agent使用skill能力绑定形成一个完整skill生态

## 出发点

anthropic Claude提出了关于一新范式skills的相关规范来扩展大模型的功能 [Agent Skills ](https://code.claude.com/docs/en/skills)

但存在问题是我并没有寻找到anthropic Claude关于 模型是如何使用skills的代码实现。于是在阅读skills文档后，我决定自己实现一套skills系统来使得模型可以使用skills

期间我寻找了相关使用skill的实战与实现的资源

1. agentscope 的skill实现[Agent Skill](https://doc.agentscope.io/tutorial/task_agent_skill.html#integrating-agent-skills-with-reactagent)
2. anthropic sdk 的skill实战 [src/anthropic/resources/beta/skills](https://github.com/anthropics/anthropic-sdk-python/tree/main/src/anthropic/resources/beta/skills)
3. claude-codebooks的skill实战  [skills](https://github.com/anthropics/claude-cookbooks/tree/main/skills)
4. DeepAgents的 skill实现 [Using skills with Deep Agents](https://blog.langchain.com/using-skills-with-deep-agents/)
5. openskills的skill实现 [Universal skills loader for AI coding agents - npm i -g openskills](https://github.com/numman-ali/openskills)

## 存在的问题

但它们存在以下问题

1. 和agent框架高度耦合 并没有统一成一个一致的接口能面向所有agent框架使用
2. 部分skills的实现并没有开发源码
3. 关于各个skill文档内容 也并没有面向所有agent框架 也没有与skills实现深度绑定
4. 没有以一个统一的 轻量化的方式提供给所有agent框架
5. 冗余的不是python的外部软件生态 而大部分agent框架是由python完成的
6. 强制在system prompt给出所有skill描述。而不是模型自主地去考虑是否要查看所有skill描述并使用skill

## 想法

所以，我实现了一个skill系统，它能以非常简单的方式无缝提供给所有agent框架使用skill。同时各个skill文档内容也随着这个skill系统深度绑定，所有agent框架可以在使用skill的同时也能获取skill文档。

而要想实现上述。通过如下角度实现最为合适

1. python package 形式。几乎所有agent框架使用python。以包的形式提供skill能力和skill文档，能够让agent框架上手即用
2. 通过已有的所有agent框架的最通用的技术来实现这个skill能力。这样能保证所有agent框架都可以使用

## 优点

1. 无缝兼容所有agent框架
2. 建立在传统框架技术上
3. 只需要pip3 install skills_for_all_agent 并提供给agent一个tool即可让agent使用skill
4. 包中带有skill内容，所有通过pip3 install skills_for_all_agent后都可以通过自带的一个前端界面自动化生成自己想要的skill内容 或者上传自己的skill内容。
5. agent使用skill时可以自动使用你以及生成的skill内容或者你上传的skill内容
6. 不会强制在system prompt给它skill相关提示词。只用给它这个工具的描述。它便可以自主地决定是否要适用skills。

## 交流

如果有不足的地方想提供建议或者想一起参与的大佬。 请扫码加入微信群。欢迎大家一起交流！！！

![示例图片](image/f8a6f9fef45eedf1d6ba5adbbe03016a.jpg)
mcp_time_server_cyf_cuc 0.1.0
An MCP Server that provides a tool to get the current time with optional timezone support
License: MIT
Requires Python: <4.0,>=3.10

# MCP Time Server

An MCP Server that provides a tool to get the current time with optional timezone support.

## Features

- Provides a `get_current_time` tool to retrieve the current time
- Supports optional timezone parameter
- Simple and lightweight implementation
- Built using the Model Context Protocol (MCP)

## Installation

```bash
pip install mcp-time-server
```

## Usage

### Running the Server

```bash
mcp-time-server
```

This will start the MCP Server using the STDIO transport, which is suitable for local process communication.

### Using the `get_current_time` Tool

The server exposes a single tool called `get_current_time` that can be used by MCP clients.

#### Parameters

- `timezone` (optional): A timezone string, e.g., "Asia/Shanghai", "America/New_York"
  - If not provided, the system's default timezone will be used

#### Return Value

A formatted string representing the current time in the format: `YYYY-MM-DD HH:MM:SS.SSSSSS TIMEZONE`

#### Examples

```python
# Get current time in system default timezone
result = await mcp_client.call_tool("get_current_time")
# Example output: "2023-12-25 13:45:30.123456 EST"

# Get current time in a specific timezone
result = await mcp_client.call_tool("get_current_time", timezone="Asia/Shanghai")
# Example output: "2023-12-26 02:45:30.123456 CST"
```

## Project Structure

```
mcp-time-server/
├── mcp_time_server/
│   ├── __init__.py      # Package initialization
│   └── main.py          # Main server implementation
├── pyproject.toml       # Project configuration
├── README.md            # This file
├── LICENSE              # License file
└── .gitignore           # Git ignore file
```

## License

MIT License - see the LICENSE file for details.

## About MCP

The Model Context Protocol (MCP) is an open-source standard for connecting AI applications to external systems. For more information, visit [modelcontextprotocol.io](https://modelcontextprotocol.io).