AI Development Pipeline MCP Integration
A comprehensive Model Context Protocol (MCP) server implementation that enables seamless integration between Claude AI, VSCode, Augment, and various cloud services including Vercel, Airtable, and Square.
🚀 Features
- Local MCP Server: Direct stdio integration with Claude Desktop
- Cloud MCP Server: HTTP endpoint for web-based Claude integration
- 7 Powerful MCP Tools: File operations, shell commands, and AI agent integration
- Multi-Platform Support: Windows (PowerShell) and Unix (Bash) startup scripts
- Production Ready: Vercel deployment configuration included
📋 Prerequisites
- Node.js 18+ and npm
- TypeScript and ts-node
- Claude Desktop (for local integration)
- Vercel account (for cloud deployment)
🛠️ Installation
- Clone the repository:
git clone https://github.com/yourusername/ai-development-pipeline-mcp.git
cd ai-development-pipeline-mcp
- Install dependencies:
- Configure environment variables:
cp .env.example .env
# Edit .env with your API keys and configuration
🔧 Configuration
Create a .env file in the root directory with the following variables:
# Vercel Configuration
VERCEL_TOKEN=your_vercel_token_here
VERCEL_PROJECT_ID=your_project_id_here
# Airtable Configuration
AIRTABLE_API_KEY=your_airtable_api_key_here
AIRTABLE_BASE_ID=your_base_id_here
AIRTABLE_TABLE_NAME=your_table_name_here
# Square Configuration
SQUARE_APPLICATION_ID=your_square_app_id_here
SQUARE_ACCESS_TOKEN=your_square_access_token_here
# Analytics Configuration
ANALYTICS_SECRET=your_analytics_secret_here
NEXT_PUBLIC_APP_URL=https://your-app-url.vercel.app
🖥️ Local MCP Server Setup
For Windows (PowerShell):
For Unix/Linux/macOS (Bash):
chmod +x start-mcp.sh
./start-mcp.sh
Manual Start:
npx ts-node local-mcp-server.ts
🔗 Claude Desktop Integration
- Start the local MCP server using one of the methods above
- Configure Claude Desktop by adding the following to your Claude Desktop configuration:
{
"mcpServers": {
"ai-development-pipeline": {
"command": "npx",
"args": ["ts-node", "/path/to/your/project/local-mcp-server.ts"],
"env": {}
}
}
}
- Restart Claude Desktop to load the MCP server
☁️ Cloud Deployment (Vercel)
Automatic Deployment (Recommended)
- Connect to GitHub:
- Go to Vercel Dashboard
- Click "New Project" and import your GitHub repository
- Vercel will automatically detect the configuration
- Manual Deployment:
npm install -g vercel
vercel deploy --prod
Build Configuration
The project includes a vercel.json configuration that handles:
- TypeScript compilation
- API route setup
- CORS headers
- Output directory configuration
Environment Variables
Configure these in your Vercel dashboard:
AIRTABLE_API_KEYAIRTABLE_BASE_IDAIRTABLE_TABLE_NAMESQUARE_ACCESS_TOKENSQUARE_APPLICATION_IDNEXTAUTH_SECRETMCP_API_KEY- All other variables from
.env.example
Claude Integration
Add to Claude as an HTTP MCP server:
- URL:
https://your-app.vercel.app/api/mcp - Method: POST
- Headers:
Content-Type: application/json
The server provides 7 powerful tools for AI-driven development:
read_project_file - Read files from the workspacewrite_project_file - Write/update files in the workspace run_shell_command - Execute shell commands (npm, git, etc.)check_file_exists - Check if files existlist_directory_files - List directory contentsrun_augment_prompt - Send prompts to Augment coding agentrun_project_tests - Execute project tests
📁 Project Structure
ai-development-pipeline-mcp/
├── app/
│ └── api/
│ └── mcp/
│ └── route.ts # Cloud MCP endpoint
├── src/
│ └── hello.ts # Example TypeScript module
├── local-mcp-server.ts # Local MCP server implementation
├── start-mcp.sh # Unix startup script
├── start-mcp.ps1 # Windows startup script
├── package.json # Dependencies and scripts
├── tsconfig.json # TypeScript configuration
├── .env.example # Environment template
└── README.md # This file
🧪 Testing
Run the TypeScript compiler to check for errors:
Test the local MCP server:
npx ts-node local-mcp-server.ts
🔒 Security Considerations
- Never commit
.env files - They contain sensitive API keys - Use environment variables for all secrets in production
- Review API permissions before deploying to production
- Enable proper authentication for cloud deployments
🤝 Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
📝 License
This project is licensed under the MIT License - see the LICENSE file for details.
🆘 Troubleshooting
Common Issues:
"Module not found" errors:
- Ensure all dependencies are installed:
npm install - Check TypeScript configuration in
tsconfig.json
MCP server won't start:
- Verify Node.js version (18+ required)
- Check that ts-node is available:
npx ts-node --version
Claude Desktop integration issues:
- Ensure the MCP server is running before starting Claude
- Check the file path in Claude Desktop configuration
- Restart Claude Desktop after configuration changes
Getting Help:
📊 Project Status
✅ Ready for Production
- Local MCP server fully functional
- Cloud deployment configured
- All 7 MCP tools tested and validated
- Cross-platform startup scripts included
- Comprehensive documentation provided
Built with ❤️ for the AI development community