MCP GitHub Repository Creator
A Model Context Protocol (MCP) server that provides tools for AI applications like GitHub Copilot to analyze repositories and create GitHub repositories automatically.
🚀 Features
- Repository Analysis: Automatically analyze local git repositories to extract metadata. Includes traditional and AI approaches to analyze the repository
- GitHub Integration: Create private GitHub repositories with proper configuration
- Topic Management: Automatically add relevant topics based on project analysis
- MCP Compatible: Works with any MCP-compatible AI client (Copilot, Claude, etc.)
- Automated Setup: Complete workflow from analysis to GitHub repository creation
📦 Installation
- Clone this repository:
git clone https://github.com/flickleafy/mcp-github-repo-creator.git
cd mcp-github-repo-creator
- Run the setup script:This will:
- Create a Python virtual environment
- Install the MCP SDK and dependencies
- Set up the project for use
🛠 Usage
As an MCP Server (Recommended)
The server provides the following tools for AI applications:
get_repo_analysis_instructions - Get detailed instructions for repository analysisanalyze_and_generate_metadata_file - Analyze repository and generate metadatacreate_github_repo_from_metadata - Create GitHub repository from metadata JSONcreate_github_repository - Create repository using existing metadata file full_repository_setup - Complete workflow: analyze → create → connect
Starting the MCP Server
# Activate virtual environment
source venv/bin/activate
# Start the MCP server
python server.py
The server runs on stdio transport and is compatible with MCP clients like:
- GitHub Copilot
- Claude Desktop
- VS Code extensions
- Custom MCP clients
MCP Client Integration
Configure your MCP client to connect to this server:
{
"name": "github-repo-creator",
"command": "python",
"args": ["server.py"],
"cwd": "/path/to/mcp-github-repo-creator"
}
Manual Usage (Alternative)
You can also use the underlying functionality directly:
# Activate virtual environment
source venv/bin/activate
# Interactive mode
python create_github_repo.py
# Direct repository creation
python create_github_repo.py --create
# Manage topics only
python create_github_repo.py --manage-topics
🎯 Workflow
- Analysis: The AI analyzes your repository structure, README, dependencies, and code
- Metadata Generation: Creates a
github_repo_metadata.json with repository details - Repository Creation: Uses GitHub CLI to create a private repository
- Configuration: Sets up topics, enables features, and connects local repository
- Push: Pushes your local code to the new GitHub repository
🔄 Detailed Workflow Types
The MCP server supports three main workflow approaches:
🤝 Interactive Copilot Workflow (Recommended)
This approach gives Copilot more control and allows for customization:
- Request Analysis Instructions: Ask Copilot to analyze the repository
- Copilot uses
get_repo_analysis_instructions - Gets detailed instructions on what to analyze
- Analyzes your repository structure, README, and code
- Generate Metadata: Copilot creates the metadata JSON
- Based on its analysis, Copilot generates repository metadata
- You can review and modify the metadata before proceeding
- Create Repository: Copilot creates the GitHub repository
- Uses
create_github_repo_from_metadata with the generated metadata - Creates repository, pushes code, and configures settings
Example Chat:
"Please analyze this repository and create a GitHub repository for it.
I want to review the metadata before you create the repo."
⚡ Full Automation Workflow
For complete automation without interaction:
- Single Command Setup: Use the
full_repository_setup tool- Analyzes repository automatically
- Generates metadata file
- Creates GitHub repository
- Connects and pushes code
- All in one step
Example Chat:
"Automatically set up this project on GitHub with full automation."
🛠️ Manual/Step-by-Step Workflow
For granular control over each step:
- Generate Metadata File:
analyze_and_generate_metadata_file - Review/Edit the generated
github_repo_metadata.json - Create Repository:
create_github_repository
Example Chat:
"First, generate a metadata file for this repository. I want to review it before creating the GitHub repo."
💬 Usage Examples with Copilot
Once configured, you can use these natural language commands with Copilot:
Analyze Repository
"Analyze this repository and tell me what metadata would be generated for GitHub."
"Generate a github_repo_metadata.json file for this repository."
Create GitHub Repository
"Create a GitHub repository for this local project. First analyze it, generate metadata, then create the GitHub repo and connect everything."
Full Setup
"Set up this entire project on GitHub - analyze the code, create appropriate metadata, and create the repository."
Step-by-Step Example
"Please create a GitHub repository for this project. Analyze the code,
generate appropriate metadata, and set up the repository on GitHub."
Copilot will:
- Analyze your project structure and code
- Detect the programming language and frameworks
- Generate topics and description
- Create
github_repo_metadata.json - Create the GitHub repository
- Connect your local repo to GitHub
- Push your code
🚀 Copilot Integration & Installation
Prerequisites for Copilot Integration
- GitHub Copilot subscription (Individual, Business, or Enterprise)
- VS Code with GitHub Copilot extension
- GitHub CLI installed and authenticated
Method 1: VS Code Copilot Integration (Recommended)
- Install GitHub CLI:
# macOS
brew install gh
# Ubuntu/Debian
sudo apt install gh
# Windows (using winget)
winget install GitHub.cli
- Authenticate GitHub CLI:
- Clone and setup this MCP server:
git clone https://github.com/flickleafy/mcp-github-repo-creator.git
cd mcp-github-repo-creator
bash setup.sh
- Configure VS Code settings (add to your VS Code settings.json):
{
"github.copilot.enable": {
"*": true,
"mcp": true
},
"mcp.servers": {
"github-repo-creator": {
"command": "python",
"args": ["server.py"],
"cwd": "/full/path/to/mcp-github-repo-creator",
"env": {
"PATH": "/full/path/to/mcp-github-repo-creator/venv/bin:${env:PATH}"
}
}
}
}
Method 2: Claude Desktop Integration
- Install Claude Desktop from claude.ai
- Configure Claude Desktop (edit
~/.config/claude-desktop/config.json):{
"mcpServers": {
"github-repo-creator": {
"command": "python",
"args": ["/full/path/to/mcp-github-repo-creator/server.py"],
"env": {
"PATH": "/full/path/to/mcp-github-repo-creator/venv/bin"
}
}
}
}
- Restart Claude Desktop and start using the commands
Automatic Installation Script
Create an easy installation script by running:
# Download and run the auto-installer
curl -sSL https://raw.githubusercontent.com/flickleafy/mcp-github-repo-creator/main/install-copilot.sh | bash
Or manually create the installer script in your project:
# Create installer script
cat > install-copilot.sh << 'EOF'
#!/bin/bash
echo "🚀 Installing MCP GitHub Repository Creator for Copilot..."
# Check dependencies
command -v python3 >/dev/null 2>&1 || { echo "❌ Python 3 is required but not installed."; exit 1; }
command -v git >/dev/null 2>&1 || { echo "❌ Git is required but not installed."; exit 1; }
# Install GitHub CLI if not present
if ! command -v gh &> /dev/null; then
echo "📦 Installing GitHub CLI..."
if [[ "$OSTYPE" == "darwin"* ]]; then
brew install gh
elif [[ "$OSTYPE" == "linux-gnu"* ]]; then
sudo apt update && sudo apt install gh
else
echo "⚠️ Please install GitHub CLI manually: https://cli.github.com/"
exit 1
fi
fi
# Clone repository
INSTALL_DIR="$HOME/.mcp-servers/github-repo-creator"
echo "📁 Installing to $INSTALL_DIR..."
mkdir -p "$HOME/.mcp-servers"
git clone https://github.com/flickleafy/mcp-github-repo-creator.git "$INSTALL_DIR"
# Setup virtual environment
cd "$INSTALL_DIR"
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
# Create VS Code configuration
VSCODE_CONFIG="$HOME/.config/Code/User/settings.json"
echo "⚙️ Adding VS Code configuration..."
# Add MCP server configuration to VS Code settings
echo "✅ Installation complete!"
echo "🔧 Next steps:"
echo "1. Authenticate with GitHub: gh auth login"
echo "2. Restart VS Code"
echo "3. Start using Copilot with MCP commands!"
EOF
chmod +x install-copilot.sh
Testing the Integration
- Open a git repository in VS Code
- Start a chat with Copilot and try:
"Use the MCP GitHub Repository Creator to analyze this repository and create a GitHub repo for it."
- Copilot should respond with repository analysis and offer to create the GitHub repository
📋 Requirements
- Python 3.8+
- Git repository (local)
- GitHub CLI (
gh) installed and authenticated - Internet connection for GitHub API calls
GitHub CLI Setup
Install and authenticate GitHub CLI:
# Install GitHub CLI (see https://cli.github.com/)
# macOS
brew install gh
# Ubuntu/Debian
sudo apt install gh
# Authenticate
gh auth login
🔧 MCP Integration
This server implements the Model Context Protocol specification, making it compatible with various AI applications:
- Repository Analysis: Extracts project metadata automatically
- GitHub Repository Creation: Creates repositories with proper settings
- Topic Management: Adds relevant topics based on analysis
- Complete Workflow: End-to-end repository setup
Supported Transports
- stdio (default): Standard input/output for direct integration
- Compatible with FastMCP framework for easy deployment
📁 Project Structure
mcp-github-repo-creator/
├── server.py # Main MCP server using FastMCP
├── core/
│ ├── repository_analyzer.py # Repository analysis logic
│ └── templates.py # String templates for messages and instructions
├── create_github_repo.py # Legacy standalone script
├── demo.py # Demo MCP client
├── requirements.txt # Dependencies including MCP SDK
├── setup.sh # Environment setup script
├── pyproject.toml # Optional project metadata
├── .gitignore # Git ignore rules
└── README.md # This file
Core Modules
server.py: Main MCP server that exposes tools to AI clientscore/repository_analyzer.py: RepositoryAnalyzer class for analyzing repository structure and generating metadata core/templates.py: Centralized template functions for all long string messages and instructionscreate_github_repo.py: Legacy standalone script (for direct usage)demo.py: Example client showing how to interact with the MCP server
The server generates metadata in this format:
{
"repository_name": "my-awesome-project",
"description": "🚀 A powerful tool for automating GitHub repository creation",
"topics": ["python", "automation", "github", "mcp", "ai-tools"],
"created_date": "2025-01-01",
"project_type": "CLI Tool",
"primary_language": "Python",
"license": "GPL-3.0",
"features": [
"Command-line interface",
"GitHub integration",
"Automated analysis"
]
}
🎯 Supported Project Types
The MCP server automatically detects and properly categorizes various project types:
- AI/ML Projects: Detects TensorFlow, PyTorch, scikit-learn, Transformers, Langchain
- Web Applications: React, Vue, Angular, Svelte, Flask, Django, FastAPI, Express, Next.js
- CLI Tools: Command-line applications and utilities
- APIs: RESTful services, GraphQL, and microservices
- Mobile Apps: React Native, Flutter, Ionic
- Desktop Apps: Electron, Tauri, PyQt, Tkinter
- Libraries: Software packages, frameworks, and SDKs
- Game Development: Unity, Godot, Pygame
- DevOps Tools: Docker, Kubernetes, Terraform configurations
- Data Science: Jupyter notebooks, data analysis projects
🌐 Language Detection
Automatically detects and supports a wide range of programming languages:
Primary Languages: Python, JavaScript, TypeScript, Java, C++, C#, Go, Rust, PHP, Ruby, Swift, Kotlin, Scala, R, Shell/Bash
Web Technologies: HTML, CSS, Vue, React (JSX/TSX), Svelte, SCSS/Sass, Less
Specialized: SQL, YAML, TOML, JSON, Dockerfile, Makefile
The analyzer examines file extensions, dependencies, and project structure to accurately determine the primary language and technology stack.
🛡️ Security & Privacy
- Secure Authentication: Uses GitHub CLI for secure, token-based authentication
- Private by Default: Creates private repositories by default for security
- No Data Storage: No sensitive data stored in metadata files
- Local Processing: Repository analysis happens locally on your machine
- GitHub Best Practices: Follows GitHub's security recommendations
- Token Scope: Uses minimal required permissions through GitHub CLI
⚠️ Limitations
- GitHub CLI Required: Must have GitHub CLI installed and authenticated
- Git Repository Required: Must be run from within a git repository with commits
- Private Repositories: Creates private repositories only (can be changed manually after creation)
- GitHub API Limits: Subject to GitHub API rate limits
- Topic Restrictions: Limited to repositories that fit GitHub's topic requirements (20 topics max)
- Network Dependency: Requires internet connection for GitHub API calls
🔧 Error Handling
The MCP server provides comprehensive error handling with clear messages for common issues:
Repository Errors
- Missing git repository: Clear instructions to initialize git
- No commits: Guidance to make initial commit
- Untracked files: Prompts to add and commit files
Authentication Errors
- GitHub CLI not found: Installation instructions
- Not authenticated: Authentication setup guidance
- Token expired: Re-authentication steps
GitHub API Errors
- Repository name conflicts: Suggestions for alternative names
- Permission issues: Troubleshooting steps
- Rate limiting: Wait time recommendations
🆘 Troubleshooting
Common Issues and Solutions
"Not a git repository" Error
# Initialize git repository
git init
# Add files and make initial commit
git add .
git commit -m "Initial commit"
"GitHub CLI not authenticated" Error
# Check authentication status
gh auth status
# Re-authenticate if needed
gh auth login
"Permission denied" Error
Solutions:
- Check GitHub CLI authentication:
gh auth status - Ensure you have permission to create repositories in your account
- Verify your GitHub token has appropriate scopes
- For organization repositories, check organization permissions
"Repository name already exists" Error
Solutions:
- Choose a different repository name
- Check your GitHub account for existing repositories
- Use the suggested alternative names from the error message
- Add a suffix or prefix to make the name unique
"GitHub API rate limit exceeded" Error
Solutions:
- Wait for the rate limit to reset (usually 1 hour)
- Use authenticated requests (ensure
gh auth login is completed) - For high-volume usage, consider GitHub API rate limit best practices
Solutions:
- Check the generated
github_repo_metadata.json for syntax errors - Ensure all required fields are present
- Validate JSON format using a JSON validator
- Re-run the metadata generation tool
"Network connectivity issues" Error
Solutions:
- Check internet connection
- Verify GitHub.com is accessible
- Check for firewall or proxy issues
- Try again after network issues are resolved
🤝 Contributing
- If you like the project give a ⭐ to the repository
- Create a feature branch, Make your changes, Submit a pull request
- Ensure your code follows the project's coding standards
- Add tests for new features or bug fixes
- Update documentation as needed
📜 License
This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.
🔗 Links
Built with ❤️ using the Model Context Protocol