Amazon Bedrock AgentCore enables you to deploy and operate AI agents securely at scale using any framework and model. AgentCore provides tools and capabilities to make agents more effective, purpose-built infrastructure to securely scale agents, and controls to operate trustworthy agents. This CLI helps you create, develop locally, and deploy agents to AgentCore with minimal configuration.

• Node.js 20.x or later
• uv for Python agents (install)

Upgrading from the Bedrock AgentCore Starter Toolkit? If the old Python CLI is still installed, you'll see a warning after install asking you to uninstall it. Both CLIs use the agentcore command name, so having both can cause confusion. Uninstall the old one using whichever tool you originally used:

pip uninstall bedrock-agentcore-starter-toolkit    # if installed via pip
pipx uninstall bedrock-agentcore-starter-toolkit   # if installed via pipx
uv tool uninstall bedrock-agentcore-starter-toolkit # if installed via uv

npm install -g @aws/agentcore

Use the terminal UI to walk through all commands interactively, or run each command individually:

# Launch terminal UI
agentcore

# Create a new project (wizard guides you through agent setup)
agentcore create
cd my-project

# Test locally
agentcore dev

# Deploy to AWS
agentcore deploy

# Test deployed agent
agentcore invoke

Note: Run agentcore deploy after add or remove to update resources in AWS.

Create agents with --with-config-bundle to auto-wire config bundle support into the generated template.

my-project/
├── agentcore/
│   ├── .env.local          # API keys (gitignored)
│   ├── agentcore.json      # Resource specifications
│   ├── aws-targets.json    # Deployment targets
│   └── cdk/                # CDK infrastructure
├── app/                    # Application code

├── app/                    # Application code
│   └── <AgentName>/        # Agent directory
│       ├── main.py         # Agent entry point
│       ├── pyproject.toml  # Python dependencies
│       └── model/          # Model configuration

Projects use JSON schema files in the agentcore/ directory:

• agentcore.json - Agent specifications, memory, credentials, evaluators, online evals
• deployed-state.json - Runtime state in agentcore/.cli/ (auto-managed)
• aws-targets.json - Deployment targets (account, region)

• Runtime - Managed execution environment for deployed agents
• Memory - Semantic, summarization, and user preference strategies
• Credentials - Secure API key management via Secrets Manager
• Evaluations - LLM-as-a-Judge for on-demand and continuous agent quality monitoring

• CLI Commands Reference - Full command reference for scripting and CI/CD
• Configuration - Schema reference for config files
• Evaluations - Evaluators, on-demand evals, and online monitoring
• Batch Evaluation - Run evaluators across sessions at scale [preview]
• Recommendations - Optimize prompts and tool descriptions [preview]
• Config Bundles - Versioned runtime configurations [preview]
• Frameworks - Supported frameworks and model providers
• Gateway - Gateway setup, targets, and authentication
• Memory - Memory strategies and sharing
• Local Development - Dev server and debugging
• Feedback - Submit feedback from your terminal

Have a quick comment or suggestion? Send it from your terminal:

agentcore feedback "your message" --screenshot path/to/screenshot.png

The CLI will display the AWS Customer Agreement and prompt for consent before submitting. See docs/feedback.md for usage details.

For bugs, regressions, or feature requests that need discussion, open an issue on GitHub instead.

See SECURITY for reporting vulnerabilities and security information.

This project is licensed under the Apache-2.0 License.