TOBE-TOGETHER/tobe-mcp

TOBE MCP Server

A comprehensive Python MCP (Model Context Protocol) server providing specialized AI-powered tools and prompts to improve development efficiency, content creation, and learning experiences.

🌟 Features

🤖 Developer Assistant

• Software System Design: Comprehensive system architecture and implementation guidance
• Code Review: Detailed code analysis with actionable feedback
• Development Best Practices: Clean code principles and optimization strategies

🎨 UI/UX Designer

• UI Design Prototypes: Complete design solutions with detailed specifications
• Design Systems: Comprehensive design tokens and component libraries
• Accessibility Audits: WCAG compliance and inclusive design guidance
• DRD Generation: Detailed design requirement documents for developers

📚 English Teacher

• Word Lessons: Detailed vocabulary explanations with pronunciation and usage
• Vocabulary Builder: Thematic word lists and learning activities
• Grammar Explanations: Comprehensive grammar lessons with examples
• Conversation Practice: Interactive dialogue scenarios and role-play
• Reading Comprehension: Educational reading materials with questions
• Pronunciation Guide: Sound analysis and practice exercises

✍️ Article Writer

• Article Generation: Complete articles in English and Chinese
• Content Outlines: Strategic content planning and structure
• Article Editing: Content improvement and optimization
• Multilingual Content: Cultural adaptation and localization
• SEO Optimization: Search engine optimization and keyword analysis
• Content Analysis: Quality assessment and performance evaluation

🚀 Quick Start

Prerequisites

• Python 3.8 or higher
• pip package manager

Installation

1. Clone the repository

   git clone <repository-url>
   cd tobe-mcp
   

2. Install dependencies

   pip install -e .
   

3. Run the server

   tobe-mcp
   

Development Setup

1. Install development dependencies

   pip install -e ".[dev]"
   

2. Run tests

   pytest
   

3. Format code

   black src/
   isort src/
   

📖 Usage

Developer Prompts

System Design

/tobe-mcp/design "Create a web application for task management with user authentication"

Code Review

/tobe-mcp/review
# Paste your code or provide a link to review

UI/UX Design Prompts

UI Design

/tobe-mcp/UIdesign "Design a mobile app interface for food delivery with dark mode support"

Design System

/tobe-mcp/design_system "E-commerce Platform" "Modern, clean, accessible design"

Accessibility Audit

/tobe-mcp/accessibility_audit "Review the accessibility of our login form design"

English Learning Prompts

Word Lesson

/tobe-mcp/word_lesson "serendipity" "Advanced vocabulary for creative writing"

Vocabulary Builder

/tobe-mcp/vocabulary_builder "Technology" "intermediate" 15

Grammar Explanation

/tobe-mcp/grammar_explanation "Present Perfect Tense" "intermediate"

Conversation Practice

/tobe-mcp/conversation_practice "Job Interview" "intermediate" 2

Reading Comprehension

/tobe-mcp/reading_comprehension "Climate Change" "intermediate" "medium"

Pronunciation Guide

/tobe-mcp/pronunciation_guide "th sounds" "intermediate"

Article Writing Prompts

Article Generation

/tobe-mcp/article_generator "The Future of Artificial Intelligence in Healthcare" "english" "blog" "professionals" 1200

Content Outline

/tobe-mcp/content_outline "Sustainable Living Practices" "article" "long" "environmentalists"

Article Editing

/tobe-mcp/article_editor "Your article content here" "seo" "general"

Multilingual Content

/tobe-mcp/multilingual_content "Original English content" "chinese" "Chinese business culture"

SEO Optimization

/tobe-mcp/seo_optimization "Your content here" "digital marketing tips" "blog"

Content Analysis

/tobe-mcp/content_analysis "Your content here" "comprehensive"

🏗️ Project Structure

tobe-mcp/
├── src/
│   ├── prompts/
│   │   ├── developer.py          # Software development prompts
│   │   ├── ui_designer.py        # UI/UX design prompts
│   │   ├── english_teacher.py    # English learning prompts
│   │   └── article_writer.py     # Content creation prompts
│   ├── tools/                    # Additional tools (future)
│   ├── logger.py                 # Centralized logging system
│   └── server.py                 # Main MCP server
├── docs/                         # Documentation
├── logs/                         # Application logs
├── tests/                        # Test files
├── pyproject.toml               # Project configuration
├── requirements.txt             # Production dependencies
├── requirements-dev.txt         # Development dependencies
└── setup.py                     # Package setup

🔧 Configuration

Logging

The server uses a centralized logging system with configurable levels:

from src.logger import get_logger

logger = get_logger("your_module_name")
logger.info("Your log message")

Environment Variables

• LOG_LEVEL: Set logging level (DEBUG, INFO, WARNING, ERROR)
• LOG_FILE: Specify custom log file path

🧪 Testing

Run the test suite:

# Run all tests
pytest

# Run with coverage
pytest --cov=src

# Run specific test file
pytest tests/test_server.py

📝 Development

Adding New Prompts

1. Create a new prompt file in src/prompts/

2. Follow the existing pattern:

   from mcp.server.fastmcp import FastMCP
   from src.logger import get_logger
   
   def your_prompt_function(mcp: FastMCP):
       logger = get_logger("your_prompt_name")
       
       @mcp.prompt("your_prompt_name")
       def your_prompt(param: str) -> str:
           logger.info(f"Processing: {param}")
           print(f"Processing: {param}")
           return f"Your prompt response for: {param}"
   

3. Register the prompt in src/server.py

Code Style

• Use Black for code formatting
• Use isort for import sorting
• Follow PEP 8 guidelines
• Add type hints where appropriate

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Guidelines

• Write tests for new features
• Update documentation as needed
• Follow the existing code patterns
• Ensure all tests pass before submitting

📄 License

This project is licensed under the Apache License 2.0 - see the file for details.

🙏 Acknowledgments

• Built with MCP (Model Context Protocol)
• Powered by FastMCP framework
• Inspired by the need for efficient AI-powered development tools

📞 Support

For questions, issues, or contributions:

• Open an issue on GitHub
• Check the documentation in the docs/ directory
• Review the test examples for usage patterns

Made with ❤️ by the TOBE Team