aws-agents Claude Code Plugin
Claude Code PluginClaude CodeDevelopmentAI Agents & AI App DevelopmentCloud, Deployment & CI/CDThe explanation below is AI-generated. Please verify it against the sources.
It covers the full agent lifecycle, from initial project scaffolding through connecting tools and APIs, deployment, debugging, evaluation and observability, production hardening, and even agent-initiated payments. The skills load detailed reference material only when needed, keeping the working context small while still offering deep guidance. It also ships an MCP server that surfaces AWS documentation and architecture references. Setup requires the AgentCore CLI, AWS CLI credentials, Node. js 20+, and Python 3. 11+ with uv.
About the service
Amazon Web Services is a cloud computing platform, and Amazon Bedrock AgentCore is its managed runtime for building and running generative AI agents. This plugin is built around that runtime: its skills scaffold, connect, deploy, and manage agents that run on AWS infrastructure, and its bundled MCP server pulls in AWS documentation and service reference material.
What you can do with aws-agents
- Scaffold a new AI agent project and choose a framework with agents-get-started
- Add memory, integrations, VPC networking, multi-agent setups, or migrate an existing Bedrock agent with agents-build
- Connect the agent to external APIs or gateways and restrict tool access with Cedar policies via agents-connect
- Deploy the agent, handle CDK errors, rollbacks, and canary releases with agents-deploy
- Diagnose broken environments or non-working agents using agents-debug
- Evaluate agent quality, review traces, and track cost with agents-optimize
- Run through a production readiness checklist and address cold-start and limit concerns with agents-harden
- Configure an agent to make its own payments at runtime, including spend limits, with agents-pay
- Pull AWS documentation and architecture guidance on demand through the bundled awsknowledge MCP server