获取设备CPU型号的MCP上下文协议实现 (MCP Context Protocol implementation for getting device CPU model)
This server has significant definition quality gaps across all three tools. Two tools (add, getHardwareInfo) are defined in TypeScript with proper registration, but the third (search_eva_content) is defined in a separate Python file using FastMCP without visible explicit registration in the primary codebase. The add tool has a critical logic bug (returns a + b + 1 instead of a + b), suggesting inadequate testing. Descriptions vary in quality but all are under 200 characters. Parameter descriptions are minimal. No output schemas are documented. Error handling is absent, no guidance for recovery, categorization, or actionable error messages.
Add two numbers
Get system hardware information including CPU and memory
查询新世纪福音战士(EVA)动画相关内容 使用 Google 搜索引擎查询 EVA 相关信息,包括角色、剧情、设定、考察等内容。
add tool has a logic bug: returns a + b + 1 instead of a + b. The description says 'Add two numbers' but the implementation adds 1 extra. This is a critical correctness failure.
No output schemas documented for any tool. The LLM cannot know what fields to expect in responses, preventing downstream tool chaining and forcing the LLM to parse unstructured text.
search_eva_content is defined in pyMCP/server.py using FastMCP, but no Python server is launched in the main TypeScript entry point (alex-mcp.js). The tool is unreachable from the primary STDIO transport.
getHardwareInfo has empty inputSchema ({}). While this is valid for a no-parameter tool, the parameter description in the rubric template is 0 because there are no parameters to describe. However, the tool registration does not include parameter-level descriptions.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 6 | 2026-07-28+ | v2 |
| 2026-03-09 | F | 47 | - | v1 |
add tool parameters lack descriptions. The inputSchema defines 'a' and 'b' with type 'number' but no description field. Per the rubric, every parameter needs a description explaining its role and constraints.
No error handling or recovery guidance. If search_eva_content fails (API error, missing SERPER_KEY), the exception message 'e.g. 搜索出错: connection timeout' gives the LLM no actionable next step.
search_eva_content relies on an environment variable SERPER_KEY with no validation or fallback. If the key is missing, the tool fails silently with 'API error' and provides no guidance to deploy or configure the server.