xiaobenyang-mcp-2-2
## 在线新闻
本MCP服务封装了新闻相关工具。
## 工具列表
本MCP服务封装了新闻相关工具,可让模型通过标准化接口调用以下功能:
| 工具名称 | 描述 |
|-------|--------------------|
| aa | xxxx(例如:实时热点新闻查询) |
| bb | yyy(例如:新闻内容关键词提取) |
## 前置需求 | Prerequisite
Node.js 22 版本或以上。
Node.js 22 or above.
## 开始使用 | Start
### 使用 Streamable HTTP 启动 | Start by Streamable HTTP transport
```
npm start
```
### 使用 Stdio 启动 | Start by Stdio transport
```
{
"mcpServers": {
"xiaobenyang-mcp": {
"args": [
"xiaobenyang-mcp"
],
"command": "npx",
"env": {
"XBY_APIKEY": "你的实际apikey",
"MCP_ID": "1804087353852938"
}
}
}
}
```
### 使用 HTTP 启动 | Start by HTTP transport
```
{
"mcpServers": {
"xiaobenyang-mcp-stream": {
"env": {
"XBY_APIKEY": "你的实际apikey"
},
"type": "streamable_http",
"url": "https://mcp.xiaobenyang.com/1804087353852938/mcp"
}
}
}
```
### 使用 SSE 启动 | Start by SSE transport
```
{
"mcpServers": {
"xiaobenyang-sse": {
"env": {
"XBY_APIKEY": "你的实际apikey"
},
"type": "sse",
"url": "https://mcp.xiaobenyang.com/1804087353852938/sse"
}
}
}
```
## Inspector
npx @modelcontextprotocol/inspector npx xiaobenyang-mcp
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one retrieves a list of dish names, while the other fetches detailed content for a specific dish. There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool based on the task.
Both tools follow a consistent verb_noun pattern (get_all_dishes and get_dish_content), using 'get' as the verb and descriptive nouns. The naming is predictable and readable, with no deviations or mixed conventions.
With only two tools, the server feels thin and under-scoped for a dish-related domain. While it covers basic retrieval, it lacks essential operations like creating, updating, or deleting dishes, which limits its utility and coherence as a complete toolset.
The toolset is severely incomplete for a dish management domain. It only provides read operations (list and get details), missing critical CRUD functions such as create_dish, update_dish, and delete_dish. This creates significant gaps that will likely cause agent failures when trying to perform full lifecycle management.