The initial deploy-on-aws plugin handles architecture recommendations, cost estimation, and infrastructure-as-code generation without requiring developers to switch between documentation, console, and terminal.
Five-Step Deployment Automation
The plugin executes a structured workflow that analyzes your code and handles deployment end-to-end:
Analyze: Scans your codebase to identify framework (React, Express, Django), database requirements (PostgreSQL, MongoDB), and dependencies, determining whether the application needs containers, serverless functions, or traditional compute.
Recommend: Selects appropriate AWS services based on analysis. For example, a Next.js app might trigger recommendations for AWS Amplify or Lambda@Edge with CloudFront, while a Django application might suggest Elastic Beanstalk or ECS with RDS.
Estimate: Calculates projected monthly costs before provisioning resources. The agent considers instance types, data transfer, storage, and other service charges to provide budget visibility upfront.
Generate: Writes infrastructure-as-code using AWS CDK (TypeScript, Python, Java) or CloudFormation templates. The generated code includes security groups, IAM roles, networking configuration, and service integrations.
Deploy: Executes the deployment to your AWS account after confirmation, handling resource creation, configuration, and validation. The agent monitors deployment progress and reports errors.
Installation Requirements
Prerequisites: Install and configure the AWS Command Line Interface (CLI) with valid credentials. The plugin requires AWS CLI v2.0 or later with configured access keys that have permissions for the services being deployed (typically AdministratorAccess for initial testing, though least-privilege IAM policies are recommended for production use).
For Claude Users: Add the AWS Labs marketplace repository: /plugin marketplace add awslabs/agent-plugins, then install the deployment plugin: /plugin install deploy-on-aws@awslabs-agent-plugins. The plugin appears in Claude’s available tools after installation.
For Cursor Users: Open the Cursor Marketplace (Cmd/Ctrl+Shift+P → “Install Plugin”), search for deploy-on-aws, and install from the awslabs-agent-plugins collection. Cursor automatically registers the plugin’s capabilities with its agent system.
Technical Architecture
Agent plugins differ from prompt engineering approaches by packaging domain expertise into structured toolkits. AWS designed the system around two components:
Hooks: Executable functions that provide automation, validation, and guardrails. A hook might verify that generated IAM policies follow least-privilege principles, check that estimated costs fall within specified budgets, or validate that infrastructure code passes security scans before deployment.
References: Curated documentation, configuration templates, and best practices that agents consult during decision-making. Rather than relying on training data that may be outdated, references provide current AWS service documentation, pricing data, and architecture patterns directly to the agent.
This architecture keeps prompts concise while maintaining access to specialized knowledge. The agent queries references when analyzing code patterns and invokes hooks when actions require validation or execution.
Why This Matters for Development Workflow
Traditional deployment workflows require developers to research appropriate services, manually configure infrastructure, estimate costs through separate calculators, and write deployment code while cross-referencing documentation. Agent plugins consolidate these steps into a conversational interface within the editor.
The approach targets scenarios where developers understand application requirements but lack deep AWS expertise. Instead of learning service combinations, pricing models, and infrastructure patterns, developers describe their application and review agent-generated recommendations before deployment.
AWS positions this as extensible infrastructure for AI-assisted development. The plugin system allows packaging new capabilities—such as security scanning, compliance validation, or multi-region deployments—into modular tools that any compatible agent can use. The open-source repository enables community contributions and custom plugin development.
Current Limitations
The initial release supports basic deployment patterns but may not handle complex architectures requiring custom networking, multi-account strategies, or specific compliance requirements. Generated infrastructure code serves as a starting point that experienced developers should review before production deployment.
Cost estimates rely on standard pricing and default configurations, potentially missing nuances like Reserved Instance savings, Savings Plans, or region-specific pricing variations. The plugin currently supports English-language interactions and primarily targets common web application frameworks.
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