aidlc-mcp-tools

# AIDLC MCP Tools A Model Context Protocol (MCP) server implementation that provides AI agents with tools to interact with the AIDLC Dashboard service. This enables seamless integration between AI tools and project management workflows. ## 🚀 Features - **Project Management**: Create and manage projects through MCP - **Artifact Upload**: Upload AI-generated artifacts (epics, user stories, domain models, etc.) - **Progress Tracking**: Update project status and track completion - **Health Monitoring**: Check service availability and performance - **Batch Operations**: Handle multiple artifacts efficiently - **Amazon Q Integration**: Optimized for Amazon Q Developer workflows ## 📋 Requirements - Python 3.11+ - requests library - AIDLC Dashboard service running (for integration) ## 🛠️ Installation ### Option 1: Using uv (Recommended) ```bash # Install with uv uv pip install -e . # Or install from PyPI (when published) uv pip install mcp-tools ``` ### Option 2: Using pip ```bash # Install in development mode pip install -e . # Or install dependencies manually pip install -r requirements.txt ``` ### Option 3: Quick Setup Script ```bash ./setup.sh ``` ## 🌐 Usage ### As MCP Server (Amazon Q Integration) 1. **Configure Amazon Q MCP settings:** ```json { "mcpServers": { "aidlc-dashboard": { "command": "uvx", "args": ["--from", "aidlc-mcp-tools@latest", "aidlc-mcp-server"], "env": { "AIDLC_DASHBOARD_URL": "http://44.253.157.102:8000/api" } } } } ``` 2. **Start the MCP server:** ```bash aidlc-mcp-server ``` ## 🔧 Configuration ### Environment Variables | Variable | Description | Default | |----------|-------------|---------| | `AIDLC_DASHBOARD_URL` | Dashboard API base URL | `http://localhost:8000/api` | | `AIDLC_TIMEOUT` | Request timeout (seconds) | `30` | | `AIDLC_RETRY_ATTEMPTS` | Number of retry attempts | `3` | | `AIDLC_LOG_LEVEL` | Logging level | `INFO` | ## 📖 Available MCP Tools ### 1. aidlc_create_pr…