JulianGiraldo97/MCP-Github-To-Trello

MCP GitHub Repository Analyzer

This project demonstrates the Model Context Protocol (MCP) by creating a server that can analyze GitHub repositories, identify potential issues, and create tasks in Trello.

Use Case

The system performs the following workflow:

1. Connects to a GitHub repository
2. Analyzes the codebase for potential issues (missing documentation, security vulnerabilities, code quality issues)
3. Creates Trello cards for identified issues with appropriate labels and descriptions

Features

• GitHub Integration: Fetches repository information, code files, and issues
• AI-Powered Code Analysis: Uses OpenAI GPT-4 and Anthropic Claude for intelligent code review
• Advanced Security Analysis: Detects vulnerabilities, security issues, and best practices
• Code Quality Assessment: Evaluates maintainability, performance, and architecture
• Trello Integration: Creates organized tasks with proper categorization
• MCP Server: Exposes functionality through the Model Context Protocol

Setup

1. Set Up Virtual Environment (Recommended)

It's highly recommended to use a virtual environment to isolate dependencies:

# Create virtual environment
python3 -m venv venv

# Activate virtual environment
# On macOS/Linux:
source venv/bin/activate
# On Windows:
# venv\Scripts\activate

# Or use the provided script:
./activate_venv.sh

2. Install Dependencies

pip install -r requirements.txt

2. Environment Variables

Create a .env file with your API keys:

# GitHub API Token
GITHUB_TOKEN=your_github_token_here

# Trello API Keys
TRELLO_API_KEY=your_trello_api_key
TRELLO_TOKEN=your_trello_token
TRELLO_BOARD_ID=your_trello_board_id

# AI API Keys (Optional - for enhanced analysis)
OPENAI_API_KEY=your_openai_api_key_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

3. Get API Keys

GitHub Token:

1. Go to GitHub Settings > Developer settings > Personal access tokens
2. Generate a new token with repo permissions

Trello API:

1. Go to https://trello.com/app-key
2. Get your API key and token
3. Create a board and note its ID from the URL

AI APIs (Optional - for enhanced analysis):

1. OpenAI: Get API key from https://platform.openai.com/api-keys
2. Anthropic: Get API key from https://console.anthropic.com/

4. Run the MCP Server

# Using the main script
python main.py server

# Or using make
make run-server

Usage

Quick Start

# Run the full workflow on your repository
python main.py workflow

# Or use make
make run-workflow

# Run a quick test
python main.py test

# Set up Trello board
python main.py setup-trello

Available Commands

• python main.py server - Start the MCP server
• python main.py workflow [repo] - Run full workflow analysis
• python main.py test - Run quick test
• python main.py setup-trello - Set up Trello board
• python main.py ai-test - Test AI analysis functionality

MCP Server Tools

The MCP server provides the following tools:

• analyze_repository: Analyzes a GitHub repository and creates Trello tasks
• list_repositories: Lists repositories for a GitHub user/organization
• get_repository_info: Gets detailed information about a specific repository
• create_trello_card: Create a single Trello card

Project Structure

mcp_tests/
├── src/                   # Source code
│   ├── analyzers/         # Analysis modules
│   │   ├── github_analyzer.py
│   │   └── ai_analyzer.py
│   ├── managers/          # External service managers
│   │   └── trello_manager.py
│   ├── utils/             # Utility functions
│   └── mcp_server.py      # Main MCP server
├── tests/                 # Test files
│   ├── quick_test.py
│   ├── direct_test.py
│   └── test_my_repo.py
├── examples/              # Example scripts
│   ├── run_full_mcp_workflow.py
│   ├── setup_trello_board.py
│   └── example_client.py
├── docs/                  # Documentation
├── main.py               # Main entry point
├── config.py             # Configuration settings
├── Makefile              # Build and development tasks
├── requirements.txt      # Python dependencies
├── .env.example         # Example environment variables
└── README.md            # This file

Example Workflow

1. Start the MCP server
2. Use an MCP client to connect to the server
3. Call analyze_repository with a GitHub repository URL
4. The system will:
   • Fetch repository data
   • Analyze code for issues
   • Create Trello cards for each identified issue
   • Return a summary of actions taken

MCP Protocol

This server implements the MCP protocol, allowing AI assistants and other tools to interact with GitHub and Trello through a standardized interface. The server exposes tools that can be called by MCP clients to perform repository analysis and task management.