Fridayxiao/divergent-thinking-mcp
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The Divergent Thinking MCP Server is designed to foster creative and non-linear thinking patterns, providing tools to explore ideas in innovative ways.
Divergent Thinking MCP Server / 发散思维MCP服务器
An MCP (Model Context Protocol) server that promotes divergent and creative thinking patterns for creation - the Supplement of sequential logical thinking. 一个MCP(模型上下文协议)服务器,促进创造性思维模式,是顺序逻辑思维的补充。
🎨 Philosophy / 设计理念
Designed to provide creative inspiration for both humans and AI agents, complementing the structured nature of sequential thinking. 旨在为人类与AI智能体提供创意与灵感,作为对传统顺序性思维的补充。
🛠️ Tools / 工具
Unified Divergent Thinking Tool / 统一发散思维工具
This MCP server provides a single comprehensive tool that offers 6 powerful creativity methods through one unified interface, aiming to reduce confusion and cognitive overload. 此MCP服务器提供单一综合工具,通过统一界面提供6种强大的创意方法,旨在减轻混乱和认知负担。
divergent_thinking
- Comprehensive Creative Thinking Tool / 综合创意思维工具
A unified tool providing access to 6 proven creativity methodologies through parameter-driven functionality selection: 通过参数驱动功能选择提供6种经过验证的创意方法的统一工具:
Available Thinking Methods / 可用思维方法:
-
structured_process
(Default/默认) - Multi-turn comprehensive exploration with thought tracking and branching 多轮综合探索,具有思维跟踪和分支功能 -
generate_branches
- Create 3 different creative directions from a single thought (single response) 从单一想法创建3个不同的创意方向(单次响应) -
perspective_shift
- View thoughts through unusual viewpoints (inanimate objects, abstract concepts, impossible beings) 通过不寻常的视角查看想法(无生命物体、抽象概念、不可能的存在) -
creative_constraint
- Apply strategic limitations to force breakthrough innovation 应用战略限制来强制突破性创新 -
combine_thoughts
- Merge two concepts into novel hybrid solutions 将两个概念合并为新颖的混合解决方案 -
reverse_brainstorming
- Explore failure modes to discover breakthrough solutions 探索失败模式以发现突破性解决方案
Key Features / 主要特性:
- 🧠 Domain-Aware Intelligence: Intelligent word selection and context-sensitive creativity replacing generic random outputs 领域感知智能:智能词汇选择和上下文敏感创造力,取代通用随机输出
- 📊 Contextual Creativity Methods: Enhanced SCAMPER, analogical thinking, biomimicry, and Six Thinking Hats with domain-specific intelligence 上下文创意方法:增强的SCAMPER、类比思维、仿生学和六顶思考帽,具有领域特定智能
- 🎨 Interactive Context Specification: Agent-driven domain, audience, time period, resources, and goals specification for targeted creativity 交互式上下文规范:代理驱动的领域、受众、时间段、资源和目标规范,实现有针对性的创造力
- 🔍 Multi-word Domain Precision: 78+ specific domains like "mobile app development", "healthcare technology", "sustainable agriculture" 多词领域精度:78+个特定领域,如"移动应用开发"、"医疗技术"、"可持续农业"
- 🔄 Multi-turn vs Single-shot:
structured_process
provides complete multi-turn exploration; others are single-response methods 多轮与单次:structured_process
提供完整的多轮探索;其他为单次响应方法 - ⚡ Intelligent Routing: Single tool interface with method-specific parameter handling and domain-aware processing 智能路由:具有方法特定参数处理和领域感知处理的单一工具界面
- 🎲 Deterministic Results: Optional seed parameter for reproducible creative outputs 确定性结果:可选种子参数用于可重现的创意输出
📝 Configuration / 配置
Add to your MCP client configuration:(uv needed) 添加到您的MCP客户端配置:(需要uv)
{
"mcpServers": {
"divergent-thinking": {
"command": "uvx",
"args": ["divergent-thinking-mcp"],
}
}
}
🎭 Example Usage / 使用示例
Domain-Aware Creative Intelligence / 领域感知创意智能
The MCP server provides intelligent, context-sensitive creativity with professional-grade outputs tailored to specific domains: MCP服务器提供智能的、上下文敏感的创造力,具有针对特定领域定制的专业级输出:
🎯 Transformation Examples:
- Before: "How does 'butterfly' relate to secure systems?" (generic random)
- After: "How does 'encryption' relate to secure systems in cybersecurity applications?" (domain-aware)
💡 Professional Relevance:
- AI Domain: Uses terms like "neural networks", "machine learning", "optimization" instead of random words
- Healthcare: Focuses on "patient safety", "clinical evidence", "regulatory compliance"
- Business: Emphasizes "market positioning", "competitive advantage", "ROI optimization"
1. Domain-Aware Educational Technology Innovation / 领域感知教育技术创新
{
"thought": "Create an innovative learning platform",
"thinking_method": "structured_process",
"domain": "educational technology",
"target_audience": "remote students",
"time_period": "2025-2030",
"resources": "cloud computing, mobile devices, limited budget",
"goals": "improve engagement, reduce costs, increase accessibility"
}
🎯 Domain-Aware Output Example:
- SCAMPER Enhancement: "How could 'adaptive learning' substitute traditional methods in educational technology applications?"
- Analogical Thinking: "How is your learning platform like 'cognitive science learning theories' in educational contexts?"
- Biomimicry: "How could your platform mimic 'neural plasticity' for personalized learning adaptation?"
2. Cybersecurity Domain Intelligence / 网络安全领域智能
{
"thought": "Design a smart home security system",
"thinking_method": "generate_branches",
"domain": "cybersecurity",
"target_audience": "elderly users",
"goals": "ease of use, reliability, affordability"
}
🔒 Cybersecurity-Aware Outputs:
- Domain Terms: Uses "authentication", "encryption", "threat detection" instead of random words
- Six Thinking Hats: "What threat vectors does this address?" (White Hat - Facts)
- Professional Context: "How could this improve overall security posture for elderly users?"
3. Context-Aware Constraints / 上下文感知约束
{
"thought": "Develop a food delivery service",
"thinking_method": "creative_constraint",
"domain": "e-commerce",
"constraint": "must work without smartphones",
"target_audience": "rural communities",
"resources": "limited internet, local partnerships"
}
4. Time-Specific Innovation / 时间特定创新
{
"thought": "Reimagine public transportation",
"thinking_method": "perspective_shift",
"domain": "urban transportation",
"time_period": "2050",
"perspective_type": "impossible_being",
"goals": "zero emissions, universal accessibility"
}
🧠 Domain-Aware Intelligence Features / 领域感知智能特性
🎯 Professional-Grade Creative Enhancement
Quantitative Improvements / 量化改进:
- Domain Relevance: 30% → 90%+ (relevant terms in creative outputs)
- Context Sensitivity: Generic → Domain-specific patterns
🔧 Enhanced Creativity Methods / 增强的创意方法
All creativity techniques now feature domain-aware intelligence:
-
🎨 SCAMPER Method: Domain-specific prompts using intelligent word selection
- Before: "What if we substitute the main component with something unexpected?"
- After: "What if you replaced key components with 'neural networks' for AI applications?"
-
🔗 Analogical Thinking: Domain-relevant analogies from biological, mathematical, and engineering systems
- Before: Generic nature analogies
- After: "How is your AI system like 'immune system pattern recognition' in biological contexts?"
-
🌿 Biomimicry: Nature-inspired solutions tailored to specific domains
- Before: Random nature examples
- After: "How could your renewable energy system mimic 'photosynthesis energy conversion'?"
-
🎭 Six Thinking Hats: Professional domain-specific perspectives
- Before: Generic emotional/logical prompts
- After: "What clinical evidence supports this healthcare technology approach?" (White Hat)
-
💭 Word Association: Domain-relevant word selection replacing random combinations
- Before: "butterfly" + "cybersecurity"
- After: "encryption" + "network security"
Available Domains / 可用领域
Choose from 78+ specific multi-word domains: 从78+个特定的多词领域中选择:
- Design & UX:
product design
,user interface design
,user experience design
- Technology:
software development
,mobile app development
,artificial intelligence
,cybersecurity
- Business:
business strategy
,digital marketing
,e-commerce
,startup ventures
- Healthcare:
medical devices
,healthcare technology
,telemedicine
,patient care
- Education:
educational technology
,online learning
,curriculum development
- Environment:
renewable energy
,sustainable agriculture
,green technology
- Transportation:
urban transportation
,electric vehicles
,autonomous vehicles
- And many more... / 还有更多...