semvec/pypi-packages huggingface dataset:
openstack-mcp-server 0.1.1
获取OpenStack集群环境资源信息，包括计算、存储、网络、镜像等资源
Requires Python: >=3.10

# OpenStack MCP Server

## 总览

基于MCP（Multimodal Capability Protocol）的OpenStack资源查询服务，提供API接口查询OpenStack云平台的计算、存储、网络、镜像等资源信息。

## 功能特性

- **实时资源查询**：通过API获取OpenStack集群的最新资源状态
- **多维度信息**：支持查询计算、存储、网络、镜像等多种资源
- **灵活过滤**：支持按名称、ID等条件筛选资源
- **详细程度控制**：支持基础、详细、完整三种信息展示级别
- **标准MCP接口**：完全兼容MCP协议，可与大语言模型无缝集成

## 技术架构

- 基于Starlette和Uvicorn的高性能异步HTTP服务
- 使用OpenStack SDK与OpenStack API交互
- 通过MCP协议将OpenStack资源信息结构化提供给大语言模型
- 支持SSE流式输出，提供实时反馈

### 架构图

```
┌─────────────┐    ┌─────────────┐    ┌─────────────┐
│             │    │             │    │             │
│  AI客户端    │───▶│  MCP Server │───▶│  OpenStack  │
│  (LLM大模型) │◀───│  (本服务)    │◀───│  API        │
│             │    │             │    │             │
└─────────────┘    └─────────────┘    └─────────────┘
```

## 安装

### 环境要求

- Python 3.10+
- OpenStack环境

### 通过pip安装

```bash
pip install openstack-mcp-server
```

## 使用方法

### 启动服务

```bash
openstack-mcp-server --port 8000 --log-level INFO --auth-url 'http://<OpenStack-API-Endpoint>:5000/v3' --username '<OpenStack-Admin-User>' --password '<OpenStack-Admin-Password>'
```

服务启动后，将在`http://localhost:8000/openstack`提供MCP接口。

### 参数说明

- `--port`: 服务监听端口，默认为8000
- `--log-level`: 日志级别，可选值为DEBUG、INFO、WARNING、ERROR、CRITICAL，默认为INFO
- `--json-response`: 使用JSON响应代替SSE流，默认为False

### 接口示例

通过MCP协议，可以使用以下工具查询OpenStack资源：

#### 获取OpenStack虚拟机实例

```json
{
  "name": "get_instances",
  "arguments": {
    "filter": "web-server",
    "limit": 10,
    "detail_level": "detailed"
  }
}
```

参数说明：
- `filter`: 筛选条件，如实例名称或ID（可选）
- `limit`: 返回结果的最大数量（可选，默认100）
- `detail_level`: 返回信息的详细程度，可选值为basic、detailed、full（可选，默认detailed）

## 通过源码安装

```bash
# 克隆仓库
git clone https://github.com/wangshqly0407/openstack-mcp-server.git
cd openstack-mcp-server
# 创建虚拟环境
uv venv
# 激活虚拟环境
source .venv/bin/activate
# 初始化运行环监
uv sync
# 开启流式HTTP MCP服务器
uv run ./src/mcp_openstack_http/server.py --port 8000 --log-level INFO --auth-url 'http://<OpenStack-API-Endpoint>:5000/v3' --username '<OpenStack-Admin-User>' --password '<OpenStack-Admin-Password>'
```

## 测试验证

```bash
# 方式1：使用npx测试
npx -y @modelcontextprotocol/inspector uv run ./src/mcp_openstack_http/server.py --port 8000 --log-level INFO --auth-url 'http://<OpenStack-API-Endpoint>:5000/v3' --username '<OpenStack-Admin-User>' --password '<OpenStack-Admin-Password>'

# 方式2：使用docker测试
docker run -it --rm -p 6274:6274 -p 6277:6277 -v $(pwd):/app -w /app node:18 npx -y @modelcontextprotocol/inspector uv run ./src/mcp_openstack_http/server.py --port 8000 --log-level INFO --auth-url 'http://<OpenStack-API-Endpoint>:5000/v3' --username '<OpenStack-Admin-User>' --password '<OpenStack-Admin-Password>'
```

访问：http://localhost:6274/

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

## 扩展开发

### 添加新的资源查询工具

1. 在`src/mcp_openstack_http/server.py`中添加相应的资源获取函数
2. 在`list_tools`方法中注册新工具
3. 在`call_tool`方法中实现工具的处理逻辑

## 许可证

Apache 2.0
de4rec 0.9.0
Dual Encoder  model for recommendations of search suggests
Requires Python: >=3.10
Keywords: recsys, recommendation systems, machine learning, AI, personalization

# de4rec


## Framework

[![Framework](https://github.com/fkrasnov2/de4rec/raw/main/de4recv3.png)](https://github.com/fkrasnov2/de4rec)

## Getting Started
bash:
```console
git clone https://github.com/fkrasnov2/de4rec.git
cd de4rec
#to test in isolated env
make install test
```
## Production ready
```bash
pip install de4rec
```
mlipdockers 0.0.8
Request to docker containers in which the python enviroments for different machine learning potential usages are implemented. Using this package, one can get the predicted potential energy for any structure using any MLIP without needing to change python environments.
Requires Python: >=3.10

A docker socket allowing for multiple MLIP usages within the same python environment.  
`mlipdockers`是一个实现在同一个python环境中使用不同机器学习原子间势（MLIP）的docker接口。

Install: `pip install mlipdockers`

Integrated machine learning interatomic potentials (MLIPs) including `grace-2l` `chgnet` `mace` `orb-models` `sevenn` `eqv2`. Details can be find in https://matbench-discovery.materialsproject.org/

Our images are uploaded in the Alibaba Cloud. Therefore, to use our package, you need to register an Alibaba Cloud account at https://account.alibabacloud.com/ and install docker.  
docker镜像上传在阿里云，因此需要注册阿里云账号才能使用。

After you register your Alibaba Cloud account, go to the `Container Registry/Instances` page, follow the instruction to register for a totally free `Instance of Personal Edition`, and get your countainer registry [username] and [password] which you will need to login in to the docker registry.  
注册账号以后，进入`容器镜像服务`页面，根据提示注册免费的`个人实例`，在`个人实例`-`访问凭证`获得`docker login ...`命令，复制到本地运行进行登录便获得了访问阿里云上公开镜像的权限。

![image](https://github.com/user-attachments/assets/bd4240f8-f9d2-4f36-990b-579963a7462a)

Finally, execute the `docker login` command provided in your own `Container Registry/Instances` page, and try to run tutorial.ipynb.

Try [examples](https://github.com/HouGroup/mlipdockers/tree/main/examples) now!
ucdp-common 0.3.0
Unified Chip Design Platform - Common Modules
Requires Python: <4.0,>=3.10.0

[![PyPI Version](https://badge.fury.io/py/ucdp-common.svg)](https://badge.fury.io/py/ucdp-common)
[![Python Build](https://github.com/nbiotcloud/ucdp-common/actions/workflows/main.yml/badge.svg)](https://github.com/nbiotcloud/ucdp-common/actions/workflows/main.yml)
[![Documentation](https://readthedocs.org/projects/ucdp-common/badge/?version=stable)](https://ucdp-common.readthedocs.io/en/stable/?badge=stable)
[![Coverage Status](https://coveralls.io/repos/github/nbiotcloud/ucdp-common/badge.svg?branch=main)](https://coveralls.io/github/nbiotcloud/ucdp-common?branch=main)
[![python-versions](https://img.shields.io/pypi/pyversions/ucdp-common.svg)](https://pypi.python.org/pypi/ucdp-common)

# Unified Chip Design Platform - Common Modules

* [Documentation](https://ucdp-common.readthedocs.io/en/stable/)
* [PyPI](https://pypi.org/project/ucdp-common/)
* [Sources](https://github.com/nbiotcloud/ucdp-common)
* [Issues](https://github.com/nbiotcloud/ucdp-common/issues)

## Installation

Installing it is pretty easy:

```bash
pip install ucdp-common
```