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

Clone the repository:

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

Install dependencies:

npm install

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

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_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:

read_project_file - Read files from the workspace
write_project_file - Write/update files in the workspace
run_shell_command - Execute shell commands (npm, git, etc.)
check_file_exists - Check if files exist
list_directory_files - List directory contents
run_augment_prompt - Send prompts to Augment coding agent
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

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:

Check the Issues page
Review the MCP documentation at modelcontextprotocol.io
Join the Claude AI community discussions

🔗 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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