semvec/pypi-packages huggingface dataset:
cloud-assistant-mcp-server 0.1.0
Add your description here
Requires Python: >=3.13

# 云助手 MCP Server

云助手的 MCP Server 实现，可以自然语言驱动向云服务器实例发送和执行自定义命令，适用于ECS带内运维、故障排查、环境检测、软件管理等场景。目前支持Linux操作系统。

<table>
  <tr>
    <td>版本</td>
    <td>v0.1.0</td>
  </tr>
  <tr>
    <td>描述</td>
    <td>自然语言驱动向云服务器实例发送和执行自定义命令</td>
  </tr>
  <tr>
    <td>分类</td>
    <td>计算</td>
  </tr>
  <tr>
    <td>标签</td>
    <td> 命令执行、带内运维</td>
  </tr>
</table>

# Tools
本 MCP Server 产品提供以下 Tools:
## Tool 1: run_command
向目标实例发送命令，生成一条执行记录，等待执行完成，然后检索并返回执行结果。
**run_command工具提供命令执行的带内通道，执行模型生成的命令**。

- 调试所需的输入参数:

输入
```json
{
    "inputSchema": {
      "type": "object",
      "required": ["instance","region","command_content"],
      "properties": {
        "instance": {
          "description": "实例名称",
          "type": "string"
        },
        "region": {
          "description": "实例所在地域，默认cn-beijing，支持cn-shanghai、cn-guangzhou、ap-southeast-1等",
          "type": "string"
        },
        "command_content": {
          "description": "执行命令内容",
          "type": "string"
        }
      }
    },
    "name": "run_command",
    "description": "提供命令执行的带内通道，执行模型生成的命令"
}

```
输出：(命令的执行输出结果)
```json
{
    "type":"text",
    "text":"cloud_assistant_cmd.sh cloud_monitor_agent_cmd.sh "
}
```

- 最容易被唤起的 Prompt示例
```text
1. 查询cn-beijing地域下实例i-ydtoqt4pogh9l3bp82xx的操作系统信息
2. 查看实例i-ydtoqt4pogh9l3bp82xx的CPU使用情况
```

# 可适配平台  
方舟、cursor、claude desktop 或支持MCP server调用的其他终端

# 服务开通链接
服务类产品，无需开通

# 鉴权方式  
火山引擎AKSK鉴权体系

# 安装部署
## 系统依赖
- 安装 Python3.10或更高版本
- 安装uv
  - MacOS/Linux
  ```text
  curl -LsSf https://astral.sh/uv/install.sh | sh
  ```
  - Windows
  ```text
  powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
  ```

# 部署

UV
```json
{
  "mcpServers": {
    "mcp_server_cloud_assistant": {
      "command": "uv",
      "env": {
        "VOLC_ENDPOINT":"Volcengine OpenApi Endpoint",
        "VOLC_ACCESSKEY":"Your Volcengine access key",
        "VOLC_SECRETKEY":"Your Volcengine secret key"
      },
      "args": [
        "--directory",
        "/<your local path to mcp-servers>/mcp_server_cloud_assistant/src/mcp_server_cloud_assistant",
        "run",
        "mcp-server-cloud-assistant"
      ]
    }
  }
}
```
UVX
```json
{
  "mcpServers": {
    "mcp_server_cloud_assistant": {
      "command": "uvx",
      "env": {
        "VOLC_ENDPOINT":"Volcengine OpenApi Endpoint",
        "VOLC_ACCESSKEY":"Your Volcengine access key",
        "VOLC_SECRETKEY":"Your Volcengine secret key"
      },
      "args": [
        "--from",
        "git+https://github.com/volcengine/mcp-server#subdirectory=server/mcp_server_cloud_assistant",
        "mcp-server-cloud-assistant"
      ]
    }
  }
}
```

# License
volcengine/mcp-server is licensed under the [MIT License](https://github.com/volcengine/mcp-server/blob/main/LICENSE)
bytehouse-mcp-server 0.1.0
Add your description here
Requires Python: >=3.13

# ByteHouse MCP Server

An MCP server for ByteHouse. ByteHouse MCP Server serves as a communication bridge between large language models and ByteHouse instances, capable of efficiently transmitting information to achieve seamless docking and collaboration between the two. It also provides intelligent services throughout the entire life cycle for ByteHouse data development, query optimization, and cluster operation and maintenance. During data development, it offers precise guidance and suggestions to improve efficiency and quality. In terms of query optimization, it supports the analysis of statements and the optimization of performance. In the aspect of cluster operation and maintenance, it provides services such as monitoring the status, warning of risks, and automatic diagnosis and repair to ensure the efficient operation of the system.

## Features

### Tools

* `run_select_query`
  - Execute SQL queries on your ByteHouse cluster.
  - Input: `sql` (string): The SQL query to execute.
  - All ByteHouse queries are run with `readonly = 1` to ensure they are safe.

* `list_databases`
  - List all databases on your ByteHouse cluster.

* `list_tables`
  - List all tables in a database.
  - Input: `database` (string): The name of the database.

* `run_dml_ddl_query`
  - Execute DML or DDL queries on your ByteHouse cluster.
  - Input: `sql` (string): The SQL query to execute.

* `get_bytehouse_table_engine_doc`
  - Get ByteHouse Engine Manual.
  - Input: `doc_name` (string): The name of the doc.

## Configuration

### Running the Server

```bash
# Run the server with stdio transport (default)
mcp-bytehouse

# Run the server with SSE transport
mcp-bytehouse --transport sse
```

1. Open the Claude Desktop configuration file located at:
   - On macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
   - On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

2. Add the following:

```json
{
  "mcpServers": {
    "mcp-bytehouse": {
      "command": "uvx",
      "args": [
            "--from",
            "git+https://github.com/volcengine/mcp-server@master#subdirectory=server/mcp_server_bytehouse",
            "--python",
            "3.13",
            "mcp-bytehouse",
      ],
      "env": {
        "BYTEHOUSE_HOST": "<ByteHouse-host>",
        "BYTEHOUSE_PORT": "<ByteHouse-port>",
        "BYTEHOUSE_USER": "<ByteHouse-user>",
        "BYTEHOUSE_PASSWORD": "<ByteHouse-password>",
        "BYTEHOUSE_SECURE": "true",
        "BYTEHOUSE_VERIFY": "true",
        "BYTEHOUSE_CONNECT_TIMEOUT": "30",
        "BYTEHOUSE_SEND_RECEIVE_TIMEOUT": "30"
      }
    }
  }
}
```

## License

This project is licensed under the Apache License.
nomad-camels-driver-keysight-b2912a 0.1.2
Device driver for the Keysight B2912A precision SMU.
Requires Python: >=3.9.6

# NOMAD-CAMELS Driver for Keysight B2912A

Driver of the Keysight E5270B Precision IV Analyzer written for the measurement software [NOMAD-CAMELS](https://fau-lap.github.io/NOMAD-CAMELS/).

## Features
This driver provides voltage and current setting / reading for both channels of the instrument. The channels can be enabled/disabled and configurations like compliance levels and measurement ranges can be set. 

## Documentation

For more information and documentation visit the NOMAD-CAMELS [documentation](https://fau-lap.github.io/NOMAD-CAMELS/doc/instruments/instruments.html).