Why this server?
This server implements human-like cognitive architecture, featuring 'dual-process thinking' (intuitive and deliberative reasoning modes), which directly addresses the concept of '慢思考' (slow thinking).
Why this server?
This system provides 'structured, iterative reasoning' and 'revision mechanisms,' perfectly matching the requirements for both '慢思考' (slow thinking) and '退一步思考' (step-back thinking).
Why this server?
This server implements an enhanced sequential thinking tool with 'self-auditing thought steps' and 'branching support,' which facilitates reflective analysis ('退一步思考') for complex coding problems.
Why this server?
Specialized in metacognitive monitoring, this server detects reasoning loops and provides intelligent recovery, directly supporting '退一步思考' (thinking back a step) to refine solutions.
Why this server?
A lightweight short-term memory server explicitly designed to 'automatically stores and recalls working context, session state, and task progress,' fulfilling the '上下文记忆能力' (contextual memory capability).
Why this server?
Enables robust '上下文记忆能力' (contextual memory) by storing conversational context and domain knowledge in a persistent graph structure that survives across multiple sessions.
Why this server?
Focuses on providing time intelligence, 'persistent memory' and 'complete traceability' for AI agents, ensuring high-quality '上下文记忆能力' (contextual memory).
Why this server?
Provides a framework for 'structured, iterative reasoning' to break down complex tasks, which is central to '慢思考' (slow thinking) and controlled problem-solving.
Why this server?
Enables AI assistants to 'reflect on, critique, and continuously improve their performance,' providing a strong mechanism for '退一步思考' (reflective analysis).
Why this server?
This tool explicitly implements Anthropic's 'think' function, giving the LLM a dedicated 'space for structured thinking' and deeper '慢思考' (slow thinking) before generating a final response.