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Deep Thinking Assistant

Deep Thinking Assistant - Gemini MCP Server

A Gemini API-based MCP server that provides deep thinking and analysis. Works with AI Editor models to provide deeper analysis and insights.

Features

  • Problem analysis from multiple perspectives

  • Integrating Critical and Creative Thinking

  • Practical and concrete proposals

  • Integrating existing knowledge and providing new perspectives

  • Context-sensitive and accurate granularity

  • Critical analysis of the proposed solution and suggestions for improvement

Related MCP server: MCP Simple OpenAI Assistant

Project Structure

dive_deep/ ├── logs/ # ログファイルディレクトリ ├── dive_deep_server.py # メインサーバーファイル ├── logger_config.py # ロギング設定 ├── prompts.py # プロンプト定義 ├── requirements.txt # 依存関係 ├── .env # 環境変数設定 └── README.md # ドキュメント

set up

  1. Install dependencies:

pip install -r requirements.txt
  1. Set environment variables: Create a .env file with the following content:

GEMINI_API_KEY=your_api_key_here GEMINI_MODEL=gemini-2.0-flash

How to use

Start the server:

python dive_deep_server.py

Available Tools

deep_thinking_agent

It deepens the thought process for solving problems and provides perspectives. This tool provides a deeper understanding and multi-faceted analysis of the problem, and provides guidelines to arrive at better solutions.

Parameters:

  • instructions : Instructions from the user (required)

  • context : the context of your thought process (required)

  • model : The model name to use (default: "gemini-2.0-flash")

enhancement_agent

Analyze your code and provide practical suggestions for improvement. This tool performs a comprehensive analysis of your code in terms of quality, performance, maintainability, and more, and provides actionable improvement suggestions.

Parameters:

  • instructions : instructions for the code being reviewed (required)

  • code : A list of codes (required)

  • model : The model name to use (default: "gemini-2.0-flash")

  • temperature : Temperature parameter at generation (default: 0.7)

final_review_agent

Perform a final code review and suggest improvements. The tool critically analyzes the proposed changes and improvements to identify potential issues and opportunities for further optimization.

Parameters:

  • instructions : instructions for the code being reviewed (required)

  • code : A list of codes (required)

  • model : The model name to use (default: "gemini-2.0-flash")

  • temperature : Temperature parameter at generation (default: 0.7)

Usage Example

  1. Deepening the thought process:

response = deep_thinking_agent( instructions="このアルゴリズムの最適化方法を考えてください", context="現在の実装では時間計算量がO(n^2)となっています", model="gemini-2.0-flash" )
  1. Code improvement suggestions:

response = enhancement_agent( instructions="このコードのパフォーマンスを改善してください", code=["def example():\n # コード内容"], model="gemini-2.0-flash" )
  1. Final Review:

response = final_review_agent( instructions="実装された改善案の最終確認をお願いします", code=["def improved_example():\n # 改善されたコード"], model="gemini-2.0-flash" )

Default System Prompt

Thought-Support Prompts

The server helps you think along these lines:

  1. Problem understanding and structured thinking

    • Understanding the big picture through systems thinking

    • Decomposing a problem using MECE

    • Causal analysis (why-why analysis, fishbone diagram)

    • Stakeholder analysis and requirements organization

  2. Designing and Evaluating Solutions

    • Applying design patterns and architectural principles

    • Quantitative evaluation of trade-offs (cost vs. benefit)

    • Risk analysis and countermeasures (FMEA method)

    • Verification of feasibility (PoC strategy)

  3. Pursuit of technical excellence

    • Clean Architecture principles, loose coupling and high cohesion, proper direction of dependencies, interface abstraction

    • Optimizing code quality - Readability and maintainability - Performance and scalability - Security and robustness

    • Designing a test strategy, considering the test pyramid, boundary values and edge cases, automation and continuous verification

  4. Innovation and Creative Thinking

    • Use Lateral Thinking

    • Idea development using the SCAMPER method

    • Creative problem solving using constraints

    • Integrating new technologies with legacy systems

  5. Optimizing implementation and deployment

    • Phased Implementation Strategy

    • Technical Debt Management and Repayment Plans

    • Change impact analysis

    • Minimizing deployment risks

  6. Continuous improvement and learning

    • Setting KPIs and metrics

    • Establishing a feedback loop

    • Systematizing and sharing knowledge

    • PDCA Cycle

  7. Communication and collaboration

    • Technical clarification

    • Structuring the document

    • Knowledge sharing across teams

    • Facilitating reviews and feedback

Answer Analysis Prompt

Your responses will be analysed based on the following criteria:

  1. Logical consistency and completeness

    • Validity of assumptions and constraints

    • Consistency of logical development

    • The process of drawing conclusions

    • Identifying overlooked elements

    • Falsifiability Test

  2. Technical feasibility and optimality

    • Appropriateness of algorithms and data structures

    • Robustness of the system architecture

    • Performance and Scalability

    • Security and Reliability

    • Maintainability and Extensibility

  3. Implementation and operation

    • Development Efficiency and Productivity

    • Operational burden and costs

    • Monitoring and troubleshooting

    • Versioning and Deployment

    • Effective team collaboration

  4. Risks and challenges

    • Technical constraints and limitations

    • Security Vulnerabilities

    • Performance Bottlenecks

    • Dependency Complexity

    • Potential technical debt

  5. Business Value and Impact

    • Development and operation costs

    • Time to market

    • Impact on user experience

    • Alignment with business requirements

    • Contributing to competitive advantage

The analysis results consist of:

  1. Strengths of the proposal

    • Technical Advantages

    • Efficiency of implementation

    • Business Value

    • Innovative elements

  2. Areas for improvement

    • Technical challenges

    • Implementation Risks

    • Operational concerns

    • Scalability Limitations

  3. Specific improvement proposals

    • Short-term improvements

    • Mid- to long-term optimization

    • Alternative Approach

    • Applying best practices

  4. Additional Considerations

    • Edge cases and exception handling

    • Future Scalability

    • Security Considerations

    • Performance Optimization

  5. Implementation Roadmap

    • Task Prioritization

    • Setting Milestones

    • Define success metrics (KPIs)

    • Risk Mitigation Strategies

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security - not tested
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license - not found
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quality - not tested

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