By awslabs
Design, build, deploy, test, and debug serverless applications using AWS Lambda, API Gateway, Step Functions, and SAM/CDK, with support for event-driven architectures, long-running workflows, and cost-optimized compute via Firecracker microVMs and managed instances.
Build, manage, and operate APIs with Amazon API Gateway (REST, HTTP, and WebSocket). Triggers on phrases like: API Gateway, REST API, HTTP API, WebSocket API, custom domain, Lambda authorizer, usage plan, throttling, CORS, VPC link, private API. Also covers troubleshooting API Gateway errors (4xx, 5xx, timeout, CORS failures) and IaC templates containing API Gateway resources. For general REST API design unrelated to AWS, do not trigger.
Build resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait/callback patterns, error handling with saga pattern, testing with LocalDurableTestRunner. Triggers on phrases like: lambda durable functions, workflow orchestration, state machines, retry/checkpoint patterns, long-running stateful Lambda functions, saga pattern, human-in-the-loop callbacks, and reliable serverless applications.
Evaluate, configure, and migrate workloads to AWS Lambda Managed Instances (LMI). Triggers on: Lambda Managed Instances, LMI, capacity provider, multi-concurrency Lambda, dedicated instance Lambda, EC2-backed Lambda, cold start elimination, Graviton Lambda, instance type for Lambda, Lambda cost optimization with Reserved Instances or Savings Plans. Also trigger when users describe high-volume predictable workloads seeking cost savings, or compare Lambda vs EC2 for steady-state traffic. For standard Lambda without LMI, use the aws-lambda skill instead.
Build, run, debug, and operate applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments that run inside a container with up to 8-hour lifetimes. Triggers on: Lambda MicroVMs, Firecracker isolation, snapshot-resumable compute, suspend/resume, sandboxed or untrusted code execution, AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, isolated security scanners, long-lived sessions, or port-listening servers (gRPC, WebSocket, custom TCP). For standard event-driven Lambda functions, use the aws-lambda skill instead.
Design, build, deploy, test, and debug serverless applications with AWS Lambda. Triggers on phrases like: Lambda function, event source, serverless application, API Gateway, EventBridge, Step Functions, serverless API, event-driven architecture, Lambda trigger. For deploying non-serverless apps to AWS, use deploy-on-aws plugin instead.
Modifies files
Hook triggers on file write and edit operations
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[!IMPORTANT] Generative AI can make mistakes. You should consider reviewing all output and costs generated by your chosen AI model and agentic coding assistant. See AWS Responsible AI Policy.
[!TIP] The Agent Toolkit for AWS is now live! The Agent Toolkit for AWS is the successor to the MCP servers, plugins, and skills available on AWS Labs, and was informed by feedback from customers like you. If you're building production software using coding agents or building agents for your own customers, we recommend Agent Toolkit for AWS. It includes IAM condition keys to distinguish agent actions from human ones, CloudWatch and CloudTrail visibility, and skills that have been evaluated for accuracy and effectiveness. This repo continues to work and accept contributions. Over time, the most useful projects here will move into Agent Toolkit for AWS.
Agent Plugins for AWS equip AI coding agents with the skills to help you architect, deploy, and operate on AWS. Agent plugins are currently supported by Claude Code, Codex, and Cursor.
AI coding agents are increasingly used in software development, helping developers write, review, and deploy code more efficiently. Agent skills and the broader agent plugin packaging model are emerging as best practices for steering coding agents toward reliable outcomes without bloating model context. Instead of repeatedly pasting long AWS guidance into prompts, developers can now encode that guidance as reusable, versioned capabilities that agents invoke when relevant. This improves determinism, reduces context overhead, and makes agent behavior easier to standardize across teams. Agent plugins act as containers that package different types of expertise artifacts together. A single agent plugin can include:
As new types of expertise artifacts emerge in this space, they can be packaged into agent plugins, making the evolution transparent to developers.
To maximize the benefits of plugin-assisted development while maintaining security and code quality, follow these essential guidelines:
npx claudepluginhub awslabs/agent-plugins --plugin aws-serverlessBuild full-stack apps with AWS Amplify Gen 2 using guided workflows for authentication, data models, storage, GraphQL APIs, and Lambda functions.
Deploy applications to AWS with architecture recommendations, cost estimates, and IaC deployment. Generate validated AWS architecture diagrams as draw.io XML.
Build, train, and deploy AI models with deep AWS AI/ML expertise brought directly into your coding assistants, covering the surface area of Amazon SageMaker AI.
Guide developers through adding maps, places search, geocoding, routing, and other geospatial features with Amazon Location Service, including authentication setup, SDK integration, and best practices.
Migrate, modernize, and upgrade codebases to AWS. Transforms .NET Framework to .NET 8/10, mainframe COBOL to Java, VMware VMs to EC2, SQL Server to Aurora, and upgrades Java/Python/Node.js versions and AWS SDKs. AWS Transform - continuous modernization analyzes codebases for tech debt, security issues, and upgrade opportunities, then remediates them.
Build, deploy, and operate applications on AWS. Skills to author infrastructure-as-code (CDK, CloudFormation), use core services (Lambda, API Gateway, Step Functions, ECS/Fargate, ECR, IAM, Amazon Bedrock with Knowledge Bases and Guardrails, AWS Blocks), and complete common tasks across observability (CloudWatch, X-Ray, CloudTrail, ADOT), messaging and streaming (SQS, SNS, EventBridge, Kinesis, MSK), AWS SDKs (boto3, JS v3, Swift), and cost optimization.
Deploy applications to AWS with architecture recommendations, cost estimates, and IaC deployment. Generate validated AWS architecture diagrams as draw.io XML.
AWS service configuration and deployment automation
36 on-demand AWS and cloud skills, slash commands, agents, and security hooks for Claude Code
AWS infrastructure and CloudFormation expertise
Serverless architecture and FaaS expert for AWS Lambda, Azure Functions, and event-driven systems