An MCP server that integrates memory management (Mem0), RAG-based document search (LlamaIndex), and database connectivity for AI agents. Supports both OpenAI API and local Ollama models.
Server has 3 unique tools (save_memory, recall_memory, search_docs) listed 6 times due to duplication in the tool list. Descriptions exist but are problematic: they contain Chinese text with 'CRITICAL MUST' directives that attempt to force LLM behavior rather than document tool purpose. Descriptions are 150-200 chars but mix imperative instructions ('必须优先调用') with functional documentation. Input schemas are present with basic type info (string parameters) but lack enums, ranges, or validation constraints. No output schemas documented. No error handling guidance. No tool annotations. Naming is acceptable (verb_noun pattern) but descriptions violate the pattern:tool-description principle by prescribing LLM behavior instead of stating what the tool does.
【强制动作 / CRITICAL MUST】在编写任何代码或回答问题之前,必须优先调用此工具检索用户的代码风格、偏好和历史习惯。 参数 query: 检索关键词(如"代码风格"、"错误处理"、"习惯")。
【强制动作 / CRITICAL MUST】在编写任何代码或回答问题之前,必须优先调用此工具检索用户的代码风格、偏好和历史习惯。 参数 query: 检索关键词(如"代码风格"、"错误处理"、"习惯")。
当用户告诉你他的个人偏好、背景信息、代码习惯,或者要求你"记住"某事时,调用此工具。 参数 fact: 需要记住的具体事实。
当用户告诉你他的个人偏好、背景信息、代码习惯,或者要求你"记住"某事时,调用此工具。 参数 fact: 需要记住的具体事实。
【强制动作 / CRITICAL MUST】只要涉及数据库、密码、框架规范、命名规则等业务代码,必须调用此工具进行本地检索。绝对不能猜测密码或命名! 参数 query: 用户的提问,如"数据库规范"、"内部密码"。
【强制动作 / CRITICAL MUST】只要涉及数据库、密码、框架规范、命名规则等业务代码,必须调用此工具进行本地检索。绝对不能猜测密码或命名! 参数 query: 用户的提问,如"数据库规范"、"内部密码"。
Descriptions contain imperative LLM directives ('【强制动作 / CRITICAL MUST】必须优先调用') instead of documenting tool purpose. This violates pattern:tool-description which requires WHAT the tool does, WHEN to use it, and prerequisites, not instructions to force LLM behavior.
No output schemas documented. LLMs cannot plan downstream calls or extract structured data. Tools return free-text strings (e.g., '🧠 检索到的长期记忆:...') requiring unstructured parsing.
Input schemas lack validation constraints. 'query' and 'fact' parameters are bare strings with no length limits, enums, or format guidance. LLMs can pass arbitrary input without validation.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 45 | 2026-07-28+ | v2 |
No error handling guidance. Tools return success/failure strings but do not categorize errors as retryable, user-fixable, or fatal. No recovery suggestions provided.
Tool list contains 6 entries but only 3 unique tools (save_memory, recall_memory, search_docs appear twice each). This indicates either a data collection error or duplicate tool registration, which confuses tool discovery.