semvec/pypi-packages huggingface dataset:
iflow-mcp_clickhouse-mcp-server 0.1.0
A Model Context Protocal (MCP) server that enables secure interaction with Clickhouse. This server allows AI assistants to list tables, read data, and execute SQL queries through a controlled interface, making database exploration and analysis safer and more structured.
Requires Python: >=3.12

# ClickHouse MCP Server
A Model Context Protocal (MCP) server implement for ClickHouse.

This server provides AI assistants with a secure and structured way to explore and analyze databases. It enables them to list tables, read data, and execute SQL queries through a controlled interface, ensuring responsible database access.

# Configuration

Set the following environment variables:

```bash
CLICKHOUSE_HOST=localhost    
CLICKHOUSE_PORT=8123         
CLICKHOUSE_USER=default
CLICKHOUSE_PASSWORD=CHANGE_TO_YOUR_PASSWORD
CLICKHOUSE_DATABASE=default
```

Or via command-line args:

* `--host` the database host
* `--port` the database port
* `--user` the database username
* `--password` the database password
* `--database` the database name

# Usage
## Fake some data in clickhouse
Check the SQL in dev_contribute.md for details.
## Post your question to AI assistant in Cline
```
What is the sales volume in each region? Which product is the best - selling?
```
<img src="pics/demo.png" alt="Demo Screenshot" width="600" />

## CLINE

Configure the MCP server in VSCode, Cline extension, or other MCP client.:
Example:
```json
{
  "mcpServers": {
    "clickhouse": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/clickhouse_mcp_server",
        "run",
        "-m",
        "clickhouse_mcp_server.server"
      ],
      "env": {
        "CLICKHOUSE_HOST": "localhost",
        "CLICKHOUSE_PORT": "8123",
        "CLICKHOUSE_USER": "default",
        "CLICKHOUSE_PASSWORD": "CHANGE_TO_YOUR_PASSWORD",
        "CLICKHOUSE_DATABASE": "default"
      }
    }
    
  }
}
```

# License

APACHE - See LICENSE file for details.

# Contribute
See dev_contribute.md for details.

## Prerequisites
- Python with `uv` package manager
- ClickHouse installation
- MCP server dependencies

# Acknowledgement
This library's implementation was inspired by the following three repositories and incorporates their code, respect for the open-source spirit!
* [GreptimeTeam/greptimedb-mcp-server](https://github.com/GreptimeTeam/greptimedb-mcp-server)
* [ktanaka101/mcp-server-duckdb](https://github.com/ktanaka101/mcp-server-duckdb)
* [designcomputer/mysql_mcp_server)](https://github.com/designcomputer/mysql_mcp_server)

Thanks!
QUBIT-Driver 1.1.1
Drive adapted for the quantum control system of the Beijing Quantum Institute

# QUBIT_Driver 

Drive adapted for the quantum control system of the Beijing Quantum Institute

'QUBIT_Driver'是一个驱动库

### 使用方式

### 安装

```
$ pip install QUBIT_Driver
```


### License
## Update log
'1.1.1' 修改numpy支持的版本，添加__version__功能
'1.1' add core driver file
'1.0' first release
[MIT]
mosaic-widget 0.21.1
A Jupyter widget for Mosaic
Requires Python: >=3.10

# Mosaic Widget

[![PyPi](https://img.shields.io/pypi/v/mosaic-widget.svg)](https://pypi.org/project/mosaic-widget/)

A Jupyter widget for Mosaic. Given a declarative specification, will generate web-based visualizations while leveraging DuckDB in the Jupyter kernel. Create interactive Mosaic plots over Pandas and Polars data frames or DuckDB connections.

Learn how to install and use the widget in the [Mosaic documentation](https://uwdata.github.io/mosaic/jupyter/).

## Developer Setup

We use [uv](https://docs.astral.sh/uv/) to manage our development setup.

You can start Jupyter with `ANYWIDGET_HMR=1 uv run jupyter lab --notebook-dir=../../../dev/notebooks`.

Run `npm run build` to build the widget JavaScript code. If you want to live edit the widget code, run `npm run dev` in a separate terminal.

Run `uv run ruff check --fix` and `uv run ruff format` to lint the code.

## Publishing

Run the build with `uv build`. Then publish with `uvx twine upload --skip-existing ../../dist/*`. We publish using tokens so when asked, set the username to `__token__` and then use your token as the password. Alternatively, create a [`.pypirc` file](https://packaging.python.org/en/latest/guides/distributing-packages-using-setuptools/#create-an-account).
duckdb-server 0.21.1
A DuckDB server for Mosaic
Requires Python: >=3.10

# Mosaic DuckDB Server

[![PyPi](https://img.shields.io/pypi/v/duckdb-server.svg)](https://pypi.org/project/duckdb-server/)

A Python-based server that runs a local DuckDB instance and support queries over Web Sockets or HTTP, returning data in either [Apache Arrow](https://arrow.apache.org/) or JSON format.

_Note:_ This package provides a local DuckDB server. To instead use DuckDB-WASM in the browser, use the `wasmConnector` in the [`mosaic-core`](https://github.com/uwdata/mosaic/tree/main/packages/mosaic/mosaic-core) package.

## Installation and usage

We recommend running the server in an isolated environment with [uvx](https://docs.astral.sh/uv/). For example, to directly run the server, use:

```bash
uvx duckdb-server
```

Alternatively, you can install the server with `pip install duckdb-server`. Then you can start the server with `duckdb-server`.

## Developer Setup

We use [uv](https://docs.astral.sh/uv/) to manage our development setup.

Start the server with `uv run duckdb-server`. The server will not restart when the code changes.

Start the server in development with `npm run dev`. The server restarts when you change the code.

Run `uv run ruff check --fix` and `uv run ruff format` to lint the code.

To run the tests, use `uv run pytest`.

To set up a local certificate for SSL, use https://github.com/FiloSottile/mkcert.

## API

The server supports queries via HTTP GET and POST, and WebSockets. The GET endpoint is useful for debugging. For example, you can query it with [this url](<http://localhost:3000/?query={"sql":"select 1","type":"json"}>).

Each endpoint takes a JSON object with a command in the `type`. The server supports the following commands.

### `exec`

Executes the SQL query in the `sql` field.

### `arrow`

Executes the SQL query in the `sql` field and returns the result in Apache Arrow format.

### `json`

Executes the SQL query in the `sql` field and returns the result in JSON format.

## Publishing

Run the build with `uv build`. Then publish with `uvx twine upload --skip-existing ../../dist/*`. We publish using tokens so when asked, set the username to `__token__` and then use your token as the password. Alternatively, create a [`.pypirc` file](https://packaging.python.org/en/latest/guides/distributing-packages-using-setuptools/#create-an-account).
iflow-mcp_mcp_scholar 0.2.0
MCP Scholar for Google Scholar search
Requires Python: >=3.10

# MCP Scholar

基于MCP协议的谷歌学术搜索和分析服务。

## 功能特点

- 谷歌学术论文搜索：根据关键词搜索相关论文，并按引用量排序
- 学者主页分析：分析谷歌学术个人主页，提取引用量最高的论文
- 支持与所有支持MCP客户端集成
- 支持与Cherry Studio集成：可以作为插件在Cherry Studio中使用

## 安装方法

### 启动服务器

```bash
# 方式一：使用uvx启动
uvx mcp-scholar

# 方式二：clone仓库后使用uv run启动
uv --directory 路径\到\mcp_scholar run mcp-scholar
```

### 在Cherry Studio中使用

- 「参照官方教程：https://vaayne.com/posts/2025/mcp-guide 」
 
## 示例用法

在Cherry Studio中，可以使用以下提示：

- 「总结5篇关于人工智能的论文」
- 「分析学者主页 https://scholar.google.com/citations?user=xxxxxx 的前10篇高引论文」

## 开发说明

本项目使用MCP协议开发，基于Python SDK实现。详细信息请参考[MCP Python SDK](https://github.com/modelcontextprotocol/python-sdk)。

## 许可证

MIT
iflow-mcp_binance-mcp-server 0.1.0
Add your description here
Requires Python: >=3.13

# Binance MCP Server

这是一个基于MCP (Model Control Protocol) 的币安交易接口服务器起点代码。它提供了一系列基础的币安交易所交互能力，可以作为你开发更复杂交易策略和功能的基础。

## 功能特性

当前实现的基础功能包括：
- 实时获取加密货币价格
- 查询账户资产余额
- 下单交易（市价单）
- 查询交易历史
- 查询当前未完成订单
- 取消订单
- 获取资金费率历史
- 执行对冲套利策略
- 自动寻找套利机会

这些功能为你开发更高级的交易策略和自动化系统提供了基础构建块。你可以基于这些接口：
- 开发更复杂的交易策略
- 添加风险管理系统
- 实现更多类型的订单支持
- 扩展数据分析能力
- 添加自定义的套利策略

## 安装要求

- Python >= 3.13
- mcp[cli] >= 1.6.0
- requests >= 2.32.3

## 安装和配置

1. 克隆仓库：
```bash
git clone https://github.com/mixuechu/binance-mcp.git
cd binance-mcp-server
```

2. 创建并激活虚拟环境

3. 安装依赖：
uv sync

4. 配置MCP：
在你的MCP配置文件中（通常位于 `~/.cursor/mcp.json`）添加以下配置：

```json
{
  "binance-mcp": {
    "command": "uv",
    "args": [
      "--directory",
      "/path/to/binance-mcp-server",
      "run",
      "binance.py",
      "--binance-api-key",
      "YOUR_API_KEY",
      "--binance-secret-key",
      "YOUR_SECRET_KEY"
    ]
  }
}
```

## 使用方法

1. 确保你已经在币安创建了API密钥，并在MCP配置文件中正确配置。

2. 通过MCP客户端调用服务提供的功能：

- `get_symbol_price`: 获取某个交易对的当前价格
- `get_account_balance`: 查询特定加密货币的账户余额
- `place_market_order`: 下市价单
- `get_trade_history`: 获取交易历史
- `get_open_orders`: 查询未完成订单
- `cancel_order`: 取消订单
- `get_funding_rate_history`: 获取资金费率历史
- `execute_hedge_arbitrage_strategy`: 执行对冲套利策略
- `find_arbitrage_pairs`: 寻找套利机会

## 开发和扩展

这个项目提供了基础的交易功能框架，你可以：
1. 添加新的交易策略
2. 扩展现有功能
3. 添加更多的错误处理和日志
4. 实现更复杂的套利逻辑
5. 集成其他交易所的API

## 安全提示

- 请妥善保管你的API密钥和密钥
- 建议在使用时设置适当的API权限限制
- 在进行实际交易前，建议先在测试网络上进行测试

## 贡献

欢迎提交问题和合并请求。这个项目处于积极开发中，我们欢迎任何形式的贡献。

## 许可证

MIT