By iaroslav-ai
Build, deploy, and operate AI agents on AWS. Skills for scaffolding agents with Amazon Bedrock AgentCore, connecting tools, memory, policies, evaluation, debugging, and production hardening.
Use when measuring or improving agent quality and performance — set up evaluators, online monitoring, CI/CD quality gates, observability, or cost optimization. Triggers on: "evaluate my agent", "add evaluator", "measure quality", "quality gate", "run evals", "agent too slow", "why is it slow", "reduce latency", "set up observability", "CloudWatch dashboard", "how much does my agent cost", "cost optimization", "logs not showing up", "logs missing", "spans not found", "eval failing", "eval error", "dev traces", "local traces", "agentcore dev traces", "traces to CloudWatch". Not for debugging errors or crashes — use agents-debug. Slow but correct routes here; broken routes to debug.
Use when adding capabilities to an existing agent project — memory, app integration, VPC, multi-agent, migration, model changes, browser, code interpreter, or resource removal. Triggers on: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "auth to call agent", "streaming responses", "VPC", "VPC connectivity", "VPC error", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "after import", "migration issue", "framework for migration", "change model", "browser tool", "code interpreter", "delete agent", "tear down", "agentcore remove", "cross-account memory", "resource-based policy on memory". Not for connecting to external APIs via Gateway — use agents-connect. Not for scaffolding a new project — use agents-get-started. Not for CLI/dev server errors — use agents-debug. Strands vs LangGraph in a migration context routes here.
Use when connecting your agent to external APIs, tools, or services via Gateway, or restricting tool access with Cedar policies. Handles gateway setup, target types, outbound auth (OAuth, API key, IAM), credentials, and Cedar policy authoring. Triggers on: "connect to API", "add gateway", "connect to MCP server", "Lambda tools", "OpenAPI", "gateway target", "Cedar policy", "restrict tools", "policy engine", "gateway auth error", "store API key", "outbound credential", "env var API key", "API key None after deploy", "credential not available after deploy", "should this be a gateway target", "give my agent tools", "add tools to agent". Not for inbound auth (who can call your agent) — use agents-harden. Not for debugging agent behavior — use agents-debug. Not for VPC networking errors (agent can't reach APIs due to VPC) — use agents-build. Not for creating or hosting a new MCP server project — use agents-get-started.
Use when your agent or environment is broken — wrong answers, errors, timeouts, tool failures, or CLI issues. Reads traces and logs to diagnose root causes. Also checks prerequisites when the CLI itself isn't working. Triggers on: "agent not working", "wrong answer", "agent error", "tool call failing", "debug agent", "check logs", "read traces", "broken", "500 error", "424 error", "model access denied", "command not found", "stuck in DELETING", "maxVms exceeded", "cold start diagnosis", "cold start slow", "agentcore create error", "create failed", "exit code 7", "connection refused local dev". Not for deploy failures — use agents-deploy. Not for performance tuning without errors — use agents-optimize. Not for VPC configuration — use agents-build. Not for observability setup or missing logs — use agents-optimize.
Use when deploying your agent to AWS, or when a deploy has failed. Handles pre-flight validation, CDK/IAM/quota error diagnosis, version management, rollback, and canary deployments. Triggers on: "deploy my agent", "agentcore deploy", "deploy failed", "CDK error", "rollback", "canary deploy", "pin version", "redeploy", "deploy stuck". Not for production hardening — use agents-harden. Not for adding capabilities before deploy — use agents-build or agents-connect. Not for VPC configuration errors — use agents-build.
External network access
Connects to servers outside your machine
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Help AI coding agents build, deploy, and manage applications on AWS.
The Agent Toolkit for AWS gives AI coding agents the tools, knowledge, and guardrails they need to work with AWS services. It works with the coding agents developers already use — including Claude Code, Codex, and Kiro.
The plugins are available on the official Anthropic marketplace (claude-plugins-official) which is added to your Claude Code installation by default.
Use the following commands to install supported plugins from the toolkit:
For aws-core that covers service selection, CDK/CloudFormation, serverless, containers, storage, observability, billing, SDK usage, and deployment:
/plugin install aws-core@claude-plugins-official
For aws-agents that covers building AI agents on AWS with Amazon Bedrock and AgentCore:
/plugin install aws-agents@claude-plugins-official
For aws-data-analytics that covers data lake, analytics, and ETL workflows with S3 Tables, AWS Glue, and Athena:
/plugin install aws-data-analytics@claude-plugins-official
In your terminal:
codex plugin marketplace add aws/agent-toolkit-for-aws
Then launch Codex and run /plugins to browse and install the aws-core plugin.
Add the AWS MCP Server to your Kiro MCP configuration (.kiro/settings/mcp.json):
{
"mcpServers": {
"aws": {
"command": "uvx",
"args": [
"mcp-proxy-for-aws@latest",
"https://aws-mcp.us-east-1.api.aws/mcp",
"--metadata", "AWS_REGION=us-west-2"
]
}
}
}
Then install skills from this repository:
npx skills add aws/agent-toolkit-for-aws/skills
Prerequisites: You need uv installed. An AWS account with credentials configured locally is required for API calls and script execution, but not for documentation search or skill discovery. See the user guide for detailed setup instructions.
See the AWS MCP Server getting started guide for instructions on configuring the AWS MCP Server with your agent.
Then install skills from this repository:
npx skills add aws/agent-toolkit-for-aws/skills
Prerequisites: You need uv installed. An AWS account with credentials configured locally is required for API calls and script execution, but not for documentation search or skill discovery. See the user guide for detailed setup instructions.
Plugins bundle the AWS MCP Server configuration and agent skills into a single install for your coding agent.
| Plugin | Description |
|---|---|
| aws-core | Core AWS skills and MCP Server configuration. Covers service selection, CDK/CloudFormation, serverless, containers, storage, observability, billing, SDK usage, and deployment. Start here. |
| aws-agents | Skills for building AI agents on AWS with Amazon Bedrock and AgentCore. |
| aws-data-analytics | Skills for data lake, analytics, and ETL workflows with S3 Tables, AWS Glue, and Athena. |
Plugins are currently available for Claude Code and Codex. For other agents, configure the AWS MCP Server directly and install skills from this repository.
Agent skills are curated packages of instructions and reference materials that help agents complete specific AWS tasks. Skills are loaded on demand — agents discover and retrieve only what's relevant to the current task.
npx skills add aws/agent-toolkit-for-aws/skills
Browse the skills/ directory to see all available skills.
Recommended project-level configuration files that tell agents how to use AWS most effectively — for example, by using the AWS MCP Server, discovering available skills, or searching documentation before acting.
See rules/ for details.
The AWS MCP Server is a managed server that gives agents access to AWS through the Model Context Protocol. It provides:
Data lake, analytics, and ETL workflows with S3 Tables, AWS Glue, and Athena.
Build, deploy, and operate applications on AWS. Skills to author infrastructure-as-code, use core services, and complete common tasks.
npx claudepluginhub iaroslav-ai/agent-toolkit-for-aws --plugin aws-agentsHarness-native ECC operator layer - 67 agents, 278 skills, 94 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Reliable automation, in-depth debugging, and performance analysis in Chrome using Chrome DevTools and Puppeteer
Real-time statusline HUD for Claude Code - context health, tool activity, agent tracking, and todo progress
Memory compression system for Claude Code - persist context across sessions