By aws
Build, deploy, and operate AI agents on AWS with Amazon Bedrock AgentCore — scaffold projects, connect tools via Gateway, debug failures, deploy with rollbacks, enforce security, and evaluate agent quality.
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.
Use when a developer wants to create a new agent project or get started with AgentCore. Handles framework selection, project scaffolding, first deploy, and first invocation. Triggers on: "build an agent", "create an agent", "get started", "new project", "agentcore create", "which framework", "Strands vs LangGraph", "hello world agent", "first agent", "create MCP server", "host MCP server", "agentcore dev", "dev server", "what port", "local development". Not for adding capabilities to existing projects — use agents-build or agents-connect. Strands vs LangGraph in a migration context routes to agents-build, not here. Connecting to an existing MCP server routes to agents-connect, not here.
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.
/plugin marketplace add aws/agent-toolkit-for-aws
This allows you to install any 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@agent-toolkit-for-aws
For aws-agents that covers building AI agents on AWS with Amazon Bedrock and AgentCore:
/plugin install aws-agents@agent-toolkit-for-aws
For aws-data-analytics that covers data lake, analytics, and ETL workflows with S3 Tables, AWS Glue, and Athena:
/plugin install aws-data-analytics@agent-toolkit-for-aws
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:
npx claudepluginhub aws/agent-toolkit-for-aws --plugin aws-agentsData 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.
Authoritative, source-cited playbook that lets a coding agent autonomously design, configure, deploy, and troubleshoot production-grade AI agents on AWS - Strands Agents SDK, Amazon Bedrock (Converse, Guardrails, Knowledge Bases), and Bedrock AgentCore (Runtime, Memory, Gateway, Identity, Browser/Code Interpreter) - with Terraform-first IaC and CloudWatch/OpenTelemetry observability. Every recommendation traces to an official AWS source.
Build, deploy, and operate applications on AWS. Skills to author infrastructure-as-code, use core services, and complete common tasks.
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.
AIDLC Operations phase automation — self-improving loops, autonomous deploys, continuous evaluation, incident response, and cost governance on AWS. Humans approve at checkpoints; agents execute diagnosis, proposal, and remediation between gates.
36 on-demand AWS and cloud skills, slash commands, agents, and security hooks for Claude Code
Multi-agent orchestration with AI SDK v5 - handoffs, routing, and coordination for any AI provider (OpenAI, Anthropic, Google)