semvec/pypi-packages huggingface dataset:
sysinfo-cli 0.1.0
System information CLI for humans and AI agents
License: MIT
Requires Python: >=3.9
Keywords: cli, system, info, monitoring, devops, ai-agent

# sysinfo-cli

System information CLI for humans and AI agents.

## Install

```bash
pip install sysinfo-cli
```

## Usage

```bash
sysinfo overview          # Quick system overview
sysinfo cpu               # CPU details
sysinfo memory            # RAM and swap
sysinfo disk              # Disk usage per partition
sysinfo network           # Network interfaces
sysinfo battery           # Battery status (laptops)
sysinfo os-info           # OS details
sysinfo top               # Top processes by CPU/memory
sysinfo all               # Full system report
```

All commands support `--json` for machine-readable output:

```bash
sysinfo --json overview
sysinfo --json cpu
```

## For AI Agents

See [SKILL.md](SKILL.md) for agent-optimized documentation.

## License

MIT
claude-conversation-export-html 0.1.0
Export Claude Code conversations to self-contained HTML with interactive selection.
License: MIT
Requires Python: >=3.10
Keywords: claude, conversation, export, html, cli

# claude-conversation-export-html

将 Claude Code 的 `.jsonl` 会话导出为**自包含 HTML**。

命令名：`claude-html-start`

## 安装

```bash
pipx install claude-conversation-export-html
claude-html-start --help
```

## 快速开始

默认读取 `~/.claude/projects`：

```bash
claude-html-start
```

非交互导出单个会话：

```bash
claude-html-start -i /path/to/session.jsonl --non-interactive -o session.html
```

非交互导出目录中指定会话：

```bash
claude-html-start -i ~/.claude/projects --non-interactive -s 1,3-5 -o export.html
```

导出全部会话：

```bash
claude-html-start -i ~/.claude/projects --non-interactive --all -o export.html
```

## 参数

- `-i, --input`：输入文件或目录（默认 `~/.claude/projects`）
- `-o, --output`：输出 HTML 路径
- `-s, --select`：会话编号选择，如 `1,3-5`
- `--all`：导出全部会话
- `--title`：HTML 标题
- `--non-interactive`：关闭交互（目录输入需配合 `--all` 或 `--select`）

## 交互快捷键

- `↑/↓` 或 `j/k`：移动
- `n / p`：翻页
- `Enter` / `Space`：勾选
- `/`：筛选
- `a`：勾选当前页
- `c`：清空
- `e`：导出
- `q`：退出

## 发布（GitHub + PyPI）

仓库已包含：
- `pyproject.toml`
- `.github/workflows/ci.yml`
- `.github/workflows/publish.yml`

发布步骤：
1. 在 PyPI 创建项目 `claude-conversation-export-html`
2. 在 GitHub Actions Secrets 设置 `PYPI_API_TOKEN`
3. 更新 `pyproject.toml` 的 `version`
4. 打 tag 并推送：

```bash
git tag v0.1.1
git push origin main
git push origin v0.1.1
```
iflow-mcp_jujumilk3-ezmcp 0.0.2
Easy-to-use MCP server framework specialized for SSE.
License: MIT
Requires Python: >=3.10

# ezmcp

Easy-to-use MCP server framework specialized for SSE.

## Overview

ezmcp is a lightweight framework that makes it easy to create MCP-compatible servers using a FastAPI-like syntax. It provides a simple decorator-based API for defining tools that can be called by MCP clients.

## Features

- FastAPI-style decorator API for defining MCP tools
- Automatic parameter validation and type conversion
- Automatic generation of tool schemas from function signatures
- Built-in support for SSE transport
- FastAPI-style middleware support
- Easy integration with existing Starlette applications
- Interactive documentation page for exploring and testing tools

![docs_image](./docs/images/docs.png)

## Installation

```bash
pip install ezmcp
```

## Quick Start

```python
from ezmcp import ezmcp, TextContent

# Create an ezmcp application
app = ezmcp("my-app")

# Define a tool
@app.tool(description="Echo a message back to the user")
async def echo(message: str):
    """Echo a message back to the user."""
    return [TextContent(type="text", text=f"Echo: {message}")]

# Run the application
if __name__ == "__main__":
    app.run(host="0.0.0.0", port=8000)
```

Once the server is running, you can:
- Access the interactive documentation at `http://localhost:8000/docs`
- Connect to the SSE endpoint at `http://localhost:8000/sse`

## Middleware

ezmcp supports middleware similar to FastAPI, allowing you to add behavior that is applied across your entire application.

```python
from starlette.requests import Request

from ezmcp import TextContent, ezmcp

app = ezmcp("my-app")

@app.middleware
async def process_time_middleware(request: Request, call_next):
    """Add a header with the processing time."""
    import time
    start_time = time.perf_counter()
    response = await call_next(request)
    process_time = time.perf_counter() - start_time
    response.headers["X-Process-Time"] = str(process_time)
    return response

@app.tool(description="Echo a message back to the user")
async def echo(message: str):
    """Echo a message back to the user."""
    return [TextContent(type="text", text=f"Echo: {message}")]
```

For more information on middleware, see the [middleware documentation](docs/middleware.md).

## Documentation

For more detailed documentation, see the [ezmcp/README.md](ezmcp/README.md) file.

## License

MIT

## commands

- install for test `pdm install -G test`
- install for dev `pdm install -G dev`