MCP server providing AI search capabilities via the MIKU API
Single tool 'mikusearch' has critical definition gaps. Tool name lacks action verb prefix (should be 'search_miku' or similar). Description is in Chinese and exceeds 1024 chars when including parameter details inline. Input schema is severely incomplete: only 'query' parameter is defined with type string, but docstring mentions 'search_mode' and 'language_mode' parameters that are NOT in the schema. These undeclared parameters are hardcoded in the implementation (simple_search, zh_CN) with no way for the LLM to control them. No output schema documented. No error handling guidance. API key exposed via environment variable (correct) but no validation or error recovery documented.
执行AI搜索并返回结果 - **query**: 搜索查询内容 - **search_mode**: 搜索模式(simple_search/deep_search),默认simple_search - **language_mode**: 语言模式(zh_CN/zh_HK/en_us/ja/ko/ru/ar),默认zh_CN
Tool name 'mikusearch' does not start with action verb. Should be 'search_miku' or 'search_ai' to clearly signal intent to LLM.
Input schema is incomplete. Docstring declares 'search_mode' and 'language_mode' parameters but they are missing from the schema definition. LLM cannot control these parameters; they are hardcoded in implementation.
No output schema documented. LLM cannot predict what fields the API returns or plan downstream operations. Response is raw JSON from external API with no structure guarantee.
Description is in Chinese and mixes parameter documentation inline rather than in parameter descriptions. Parameter 'query' has description but 'search_mode' and 'language_mode' have no descriptions in schema.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 23 | 2026-07-28+ | v2 |
No error handling or recovery guidance. If API call fails (invalid key, rate limit, network error), LLM receives raw exception with no actionable next steps.