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: Customized MCP Server

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

2. 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"
)

2. 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"
)

3. 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