semvec/pypi-packages huggingface dataset:
synchromcp 1.0.4
Synchronize MCP server configurations across AI apps and machines
Requires Python: >=3.11
Keywords: ai, claude, cursor, mcp, model-context-protocol, sync

# synchromcp

Synchronize MCP (Model Context Protocol) server configurations across AI apps and machines.

## Problem

AI coding assistants store MCP server configs in different locations:
* Claude Desktop: `~/Library/Application Support/Claude/claude_desktop_config.json`
* Cursor: `~/.cursor/mcp.json`
* VSCode extensions: scattered across `globalStorage` directories
* Codex CLI: `~/.codex/config.toml` (different format!)

Keeping these in sync manually is tedious and error-prone.

## Solution

```bash
# Sync MCP servers from Claude Desktop to all other apps
synchromcp sync

# Preview changes without writing
synchromcp sync --dry-run

# Sync to external machine mounted at /Volumes/backup
synchromcp sync --mounts /Volumes/backup
```

## Installation

```bash
pip install synchromcp
```

Or with uv:

```bash
uv tool install synchromcp
```

## Usage

### List discovered config files

```bash
synchromcp list
```

Output:

```
Found 8 MCP config files:
  [source] ~/Library/Application Support/Claude/claude_desktop_config.json
  ~/.cursor/mcp.json
  ~/.boltai/mcp.json
  ~/.codex/config.toml
  ...
```

### Show current MCP servers

```bash
synchromcp show
```

Output:

```json
{
  "filesystem": {
    "command": "npx",
    "args": ["-y", "@modelcontextprotocol/server-filesystem", "~/Data"]
  },
  "memory": {
    "command": "npx",
    "args": ["-y", "@modelcontextprotocol/server-memory"]
  }
}
```

### Sync to all targets

```bash
# Dry run first
synchromcp sync --dry-run

# Apply changes
synchromcp sync
```

### Sync to external volumes

```bash
synchromcp sync --mounts /Volumes/MacMini,/Volumes/Laptop
```

This syncs to config files on mounted external drives, useful for keeping multiple machines in sync.

### Use a different source

```bash
synchromcp sync --source ~/.cursor/mcp.json
```

### Validate a config file

```bash
synchromcp validate ~/.boltai/mcp.json
```

## Supported Apps

| App | macOS | Windows | Linux |
|-----|-------|---------|-------|
| Claude Desktop | Y | Y | Y |
| Claude Code | Y | Y | Y |
| Cursor | Y | Y | Y |
| BoltAI | Y | - | - |
| Gemini CLI | Y | Y | Y |
| Codex CLI | Y | Y | Y |
| Jan | Y | Y | Y |
| VSCode Kilo Code | Y | Y | Y |
| VSCode Roo Code | Y | Y | Y |

## How It Works

1. Discovers all MCP config files on your system
2. Reads the source config (default: Claude Desktop)
3. Validates the `mcpServers` section
4. Updates only the `mcpServers` section in each target file
5. Preserves all other data in target files

### JSON vs TOML

Most apps use JSON with a `mcpServers` key:

```json
{
  "mcpServers": {
    "server-name": { "command": "...", "args": [...] }
  }
}
```

Codex CLI uses TOML with a `mcp_servers` key:

```toml
[mcp_servers.server-name]
command = "..."
args = [...]
```

synchromcp handles the conversion automatically.

## Development

```bash
git clone https://github.com/twardoch/synchromcp.git
cd synchromcp
uv venv && uv pip install -e ".[dev]"
pytest
```

## License

MIT
f1gp 0.1.0
F1GP
Requires Python: >=3.8.1
Keywords: science, exploration, research

# F1gp

## Installation

You can install f1gp using pip:

```bash
pip install f1gp
```

For development installation:

```bash
pip install -e ".[dev]"
```

## Usage

```python
import f1gp

# Your code here
```

## Features

- Feature 1
- Feature 2
- Feature 3

## Development

### Setup

1. Clone the repository:
```bash
git clone https://github.com/yourusername/f1gp.git
cd f1gp
```

2. Install development dependencies:
```bash
pip install -e ".[dev]"
```

### Running Tests

```bash
pytest
```

### Code Formatting

```bash
black f1gp tests
```

### Type Checking

```bash
mypy f1gp
```

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

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

## Publishing to PyPI

To publish this package to PyPI:

1. Install build tools:
```bash
pip install build twine
```

2. Build the package:
```bash
python -m build
```

3. Upload to TestPyPI (optional, for testing):
```bash
python -m twine upload --repository testpypi dist/*
```

4. Upload to PyPI:
```bash
python -m twine upload dist/*
```

Make sure you have a PyPI account and have configured your credentials before publishing.
iflow-mcp_winautowx 1.0.0
微信自动化脚本模拟人为操作，支持MCP
Requires Python: >=3.8

# WinAutoWx 针对 Weixin/WeChat 自动化脚本 支持 LLM 的 MCP 

本项目提供一个基于 Python + pywinauto 的自动化脚本，可在 Windows 上连接/启动微信（Weixin/WeChat），搜索好友或群聊并发送消息，支持一次性向多个好友循环发送多条消息。


![](./png/image.png)


交流群

![](./png/35c6fe96f9109015aad90f62d1b1de8b.jpg)


赞赏

![](./png/6fbe97d18b0a6992141ece2aadea0a9d.jpg)

## 启动指令速查
- 命令行（CLI 用法已迁移至 Debug 文档）
请参考 `Debug.md` 获取 `run_wechat.py` 的命令行用法与调试说明。

- 启动 HTTP API 服务（FastAPI）
```bash
uvicorn server:app --host 127.0.0.1 --port 8000
```

- 启动 fastmcp（MCP/stdio）服务并用 MCP Inspector 连接
```bash
python mcp_server.py
mcp-inspector --server "python mcp_server.py"
```

## 环境要求
- Windows 10/11（64 位推荐）
- Python 3.8–3.12（64 位推荐）
- 已安装并登录 Windows 版微信（Weixin/WeChat）

## 安装
```bash
pip install -r requirements.txt
```

## 快速上手
若需要通过命令行快速发送或调试，请查看 `Debug.md`。以下为通过 HTTP API/MCP 的方式：

## 参数说明（CLI）
命令行参数表已迁移至 `Debug.md`。

## 常见用法示例（CLI）
命令行示例已迁移至 `Debug.md`。

## 通过 API 调用（FastAPI / fastmcp 2.0）
已提供 `server.py`，可作为本地服务供 AI/HTTP 调用。

- 启动服务：
```bash
uvicorn server:app --host 127.0.0.1 --port 8000
```

- 发送消息接口：POST `http://127.0.0.1:8000/send`
```json
{
  "friends": ["文件传输助手"],
  "messages": ["测试一下"],
  "backend": "win32",
  "ctrl_enter": false,
  "friend_delay": 0.5,
  "message_delay": 0.2,
  "no_launch": false,
  "verbose": true
}
```

- 导出控件接口：POST `http://127.0.0.1:8000/dump`
```json
{
  "backend": "win32",
  "verbose": true
}
```

说明：脚本主体位于 `script/wechat_sender.py`。命令行使用说明见 `Debug.md`；HTTP 接口由 `server.py` 提供。

### 通过 fastmcp（MCP/stdio 协议）

已提供 `mcp_server.py`（基于 `fastmcp` 2.0）。它是一个 MCP 服务器，通过标准输入输出（stdio）对外暴露工具。内部会把工具调用转发到上面的 HTTP 服务。

1) 安装依赖并启动 HTTP 服务：
```bash
pip install -r requirements.txt
uvicorn server:app --host 127.0.0.1 --port 8000
```

2) 启动 MCP 服务器（stdio）：
```bash
python mcp_server.py
```

3) -用 MCP Inspector 连接：-（废弃）
```bash
mcp-inspector --server "python mcp_server.py"
```

工具说明：
- `send_messages(friends, messages, backend='uia'|'win32', ctrl_enter=False, friend_delay=0.5, message_delay=0.2, no_launch=False, verbose=False)`
- `dump_controls(backend='uia'|'win32', verbose=True)`

可用环境变量：
- `WEIXIN_API_URL`：转发的 HTTP 服务地址（默认 `http://127.0.0.1:8000`）

### MCP Inspector 配置
1) 先启动 HTTP 服务（新终端）：
```bash
uvicorn server:app --host 127.0.0.1 --port 8000
```
npx @modelcontextprotocol/inspector


2) 在 MCP Inspector 中填写：
- **Server command**:
```bash
python mcp_server.py
```
- **Working Directory**:
```bash
D:\代码存储\winautowx
```
- **Environment variables**（可选）：
  - `WEIXIN_API_URL`: `http://127.0.0.1:8000`
- **Arguments**: 留空
- **Transport**: 默认 stdio（保持不变）
- 点击 Connect

3) 在 Inspector 中调用 tools：
- `send_messages` 示例参数：
```json
{
  "friends": ["文件传输助手"],
  "messages": ["测试一下"],
  "backend": "win32",
  "ctrl_enter": false,
  "friend_delay": 0.5,
  "message_delay": 0.2,
  "no_launch": false,
  "verbose": true
}
```
- `dump_controls` 示例参数：
```json
{
  "backend": "win32",
  "verbose": true
}
```

## 使用建议
- 保持微信主窗口处于当前桌面且未最小化。
- 先用“文件传输助手”验证流程，避免打扰他人。
- 若你的微信版本为新版 Weixin（进程 `Weixin.exe`），脚本已适配。
- 特殊布局或企业微信可能与控件结构不同，遇到问题请开 `--verbose` 并将输出粘贴给我。

## 免责声明
- 此脚本仅用于学习与个人效率用途。请遵守相关平台使用条款，避免滥用自动化操作。
bankai 1.1.2
TUI to help you setup your Linux system
Requires Python: >=3.12

# Bankai Linux Setup (inspired by the anime "Bleach")

**Quick Start:**
```bash
pipx install bankai
bankai
```

Bankai is a modular, multi-distro Linux setup and configuration toolkit. It automates the installation of essential applications, developer tools, terminal configs, and user environment tweaks for several popular Linux distributions.

## Supported Distributions
- **CachyOS / Arch-based**
- **Kubuntu / Debian / Ubuntu**
- **Nobara / Fedora**

> [!NOTE]
> The current release is primarily focused on and tested with Arch-based distributions like CachyOS. , the plan for other distributions is to have them working as well, but it's not a priority. and does not work in this release.

## Features
- Automated installation of system packages and Flatpaks.
- Terminal and shell configuration (Fish, Starship, Fisher, etc.)
- IDEs, developer tools, and language managers (Rust, Node, Python, etc.)
- Optional gaming, Docker, and other productivity enhancements
- Modular config files for terminals (Kitty, Alacritty, Ghostty, Fastfetch)
- Git and SSH setup helper

## Usage
After installation, simply run the main command:
```bash
bankai
```
- The script will auto-detect your OS or prompt you to select one.
- You can specify the OS directly:
  ```bash
  bankai --os cachyos   # or kubuntu, nobara
  ```
- Any extra arguments will be passed to the OS-specific script by adding `--` before them:
  ```bash
  bankai --os cachyos -- --some-arg
  ```
- Follow the prompts for optional installs (gaming, Docker, Fish shell, etc.).

## Notes
- `pipx` is the recommended tool for installing command-line applications like Bankai, as it isolates them in their own environments. You can install it via `pip install pipx`.
- Some steps will require `sudo` privileges. The script will prompt you for your password when needed.
- A system restart or re-login is recommended for all changes to take effect.

## For Developers (Contributing)

If you want to contribute or customize the scripts, you can clone the repository:
```bash
git clone https://github.com/axatbhardwaj/bankai.git
cd bankai
# Recommended: create a virtual environment
python -m venv .venv
source .venv/bin/activate
# Install in editable mode
pip install -e .
# Now you can run your local version
bankai
```

- **Package lists** are in `common/`
- **Configuration templates** are in `configs/`
- **OS-specific logic** is in `os_scripts/`


## License
MIT (see repository)