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theburgerllc

AI Development Pipeline MCP

by theburgerllc
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TypeScript
Hybrid

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

Related MCP server: MCP-BOS

📋 Prerequisites

  • Node.js 18+ and npm

  • TypeScript and ts-node

  • Claude Desktop (for local integration)

  • Vercel account (for cloud deployment)

🛠️ Installation

  1. Clone the repository:

git clone https://github.com/yourusername/ai-development-pipeline-mcp.git cd ai-development-pipeline-mcp

  1. Install dependencies:

npm install

  1. 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):

.\start-mcp.ps1

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

  1. Start the local MCP server using one of the methods above

  2. 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": {} } } }

  1. Restart Claude Desktop to load the MCP server

☁️ Cloud Deployment (Vercel)

Automatic Deployment (Recommended)

  1. Connect to GitHub:

    • Go to Vercel Dashboard

    • Click "New Project" and import your GitHub repository

    • Vercel will automatically detect the configuration

  2. 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_KEY

  • AIRTABLE_BASE_ID

  • AIRTABLE_TABLE_NAME

  • SQUARE_ACCESS_TOKEN

  • SQUARE_APPLICATION_ID

  • NEXTAUTH_SECRET

  • MCP_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

🛠️ Available MCP Tools

The server provides 7 powerful tools for AI-driven development:

  1. read_project_file - Read files from the workspace

  2. write_project_file - Write/update files in the workspace

  3. run_shell_command - Execute shell commands (npm, git, etc.)

  4. check_file_exists - Check if files exist

  5. list_directory_files - List directory contents

  6. run_augment_prompt - Send prompts to Augment coding agent

  7. run_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:

npx tsc --noEmit

Test the local MCP server:

npx ts-node local-mcp-server.ts

🔒 Security Considerations

  • Never commit - 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

  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

📝 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:

🔗 Related Projects

📊 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

One-click Deploy
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

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