AWS IoT Greengrass AI Agents Context Pack

This repository provides structured knowledge and step-by-step guides for AI agents to quickly set up and experiment with AWS IoT Greengrass Nucleus. It follows the https://agents.md specification.

⚠️ Important Notice

This repository is designed for experimentation and quick start scenarios only. It is NOT intended for production devices or environments.

Purpose

This context pack enables AI agents to:

• Set up Greengrass Nucleus (full runtime) and Greengrass Nucleus Lite (constrained devices) in containerized environments
• Create and deploy custom IoT components
• Follow best practices for component development
• Troubleshoot common issues
• Provide guided assistance for Greengrass Nucleus experimentation

AI Agent Integration

AI agents should reference AGENTS.md for:

• Critical workflow patterns that require reading documentation before implementation
• Pre-implementation checklists to ensure proper preparation
• User interaction guidelines for verifying assumptions and providing corrections
• Quick setup references with direct links to relevant hands-on labs

Getting Started with the Agent

To understand what the AI agent can help you with, simply ask:

• "intro" or "introduction"
• "tell me what you do"
• "what can you help me with?"

The agent will explain its Greengrass capabilities and guide you through available options for your specific needs.

Supported Greengrass Variants

Greengrass Nucleus (Full Runtime)

Provides the complete IoT Greengrass experience with full component lifecycle management, advanced deployment capabilities, and comprehensive features suitable for development and testing environments.

Greengrass Nucleus Lite (Constrained Devices)

Offers a lightweight runtime optimized for resource-constrained environments with a simplified component model, edge device optimization, and rapid experimentation capabilities.

Getting Started

AI agents should follow this sequence:

1. Review AGENTS.md for workflow patterns and implementation guidelines
2. Select appropriate setup:
   • For full feature set: setup/setup-greengrass-container.md
   • For constrained environments: setup/setup-greengrass-lite-container.md
3. Implement component development: components/ and components/comprehensive-component-recipe.yaml
4. Execute deployment: setup/deploy-components-to-greengrass-lite.md

Technical Considerations

• Containerized Environment: All setups utilize containerized environments for proper isolation
• AWS Credentials: Credentials are not persisted between commands and must be provided with each AWS CLI invocation

Usage Guidelines

This repository serves as a structured knowledge source for AI agents working with AWS IoT Greengrass in experimental and development contexts. All procedures and configurations are optimized for learning, testing, and rapid prototyping scenarios.