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AI Development Pipeline MCP

by theburgerllc
README.md6.77 kB
# 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 1. **Clone the repository:** ```bash git clone https://github.com/yourusername/ai-development-pipeline-mcp.git cd ai-development-pipeline-mcp ``` 2. **Install dependencies:** ```bash npm install ``` 3. **Configure environment variables:** ```bash 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: ```env # 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): ```powershell .\start-mcp.ps1 ``` ### For Unix/Linux/macOS (Bash): ```bash chmod +x start-mcp.sh ./start-mcp.sh ``` ### Manual Start: ```bash 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: ```json { "mcpServers": { "ai-development-pipeline": { "command": "npx", "args": ["ts-node", "/path/to/your/project/local-mcp-server.ts"], "env": {} } } } ``` 3. **Restart Claude Desktop** to load the MCP server ## ☁️ Cloud Deployment (Vercel) ### Automatic Deployment (Recommended) 1. **Connect to GitHub:** - Go to [Vercel Dashboard](https://vercel.com/dashboard) - Click "New Project" and import your GitHub repository - Vercel will automatically detect the configuration 2. **Manual Deployment:** ```bash 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: ```bash npx tsc --noEmit ``` Test the local MCP server: ```bash 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 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](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](https://github.com/yourusername/ai-development-pipeline-mcp/issues) page - Review the MCP documentation at [modelcontextprotocol.io](https://modelcontextprotocol.io) - Join the Claude AI community discussions ## 🔗 Related Projects - [Model Context Protocol](https://github.com/modelcontextprotocol) - [Claude Desktop](https://claude.ai/desktop) - [Vercel](https://vercel.com) - [Airtable API](https://airtable.com/developers) ## 📊 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**

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