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:
```
bash setup.sh
```
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 analysis
analyze_and_generate_metadata_file - Analyze repository and generate metadata
create_github_repo_from_metadata - Create GitHub repository from metadata JSON
create_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 Metadata File

"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:
```
gh auth login
```

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:

Available Tools

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 clients
core/repository_analyzer.py: RepositoryAnalyzer class for analyzing repository structure and generating metadata
core/templates.py: Centralized template functions for all long string messages and instructions
create_github_repo.py: Legacy standalone script (for direct usage)
demo.py: Example client showing how to interact with the MCP server

📊 Example Metadata Structure

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

"Invalid metadata format" Error

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

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:
```
bash setup.sh
```
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 analysis
analyze_and_generate_metadata_file - Analyze repository and generate metadata
create_github_repo_from_metadata - Create GitHub repository from metadata JSON
create_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 Metadata File

"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:
```
gh auth login
```

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:

Available Tools

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 clients
core/repository_analyzer.py: RepositoryAnalyzer class for analyzing repository structure and generating metadata
core/templates.py: Centralized template functions for all long string messages and instructions
create_github_repo.py: Legacy standalone script (for direct usage)
demo.py: Example client showing how to interact with the MCP server

📊 Example Metadata Structure

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

"Invalid metadata format" Error

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