Overview

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.

🚀 Jump Into AgentCore

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

Installation

npm install -g @aws/agentcore

Public Preview: If you previously used the Bedrock AgentCore Starter Toolkit, uninstall it before using this CLI:

pip uninstall bedrock-agentcore-starter-toolkit

Quick Start

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

Supported Frameworks

| Framework | Notes | | ------------------- | ----------------------------- | | Strands | AWS-native, streaming support | | LangChain/LangGraph | Graph-based workflows | | Google ADK | Gemini models only | | OpenAI Agents | OpenAI models only |

Supported Model Providers

| Provider | API Key Required | Default Model | | -------------- | ------------------------- | ----------------------------- | | Amazon Bedrock | No (uses AWS credentials) | claude-sonnet-4-5-20250929-v1 | | Anthropic | Yes | claude-sonnet-4-5-20250929 | | Google Gemini | Yes | gemini-2.5-flash | | OpenAI | Yes | gpt-4o |

Commands

Project Lifecycle

| Command | Description | | -------- | ------------------------------ | | create | Create a new AgentCore project | | dev | Start local development server | | deploy | Deploy infrastructure to AWS | | invoke | Invoke deployed agents |

Resource Management

| Command | Description | | -------- | ------------------------------------- | | add | Add agents, memory, identity, targets | | remove | Remove resources from project |

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

Project Structure

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

App Structure

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

Configuration

Projects use JSON schema files in the agentcore/ directory:

• agentcore.json - Agent specifications, memory, identity, remote tools
• deployed-state.json - Runtime state in agentcore/.cli/ (auto-managed)
• aws-targets.json - Deployment targets (account, region)

Capabilities

• Runtime - Managed execution environment for deployed agents
• Memory - Semantic, summarization, and user preference strategies
• Identity - Secure API key management via Secrets Manager

Documentation

• CLI Commands Reference - Full command reference for scripting and CI/CD
• Configuration - Schema reference for config files
• Frameworks - Supported frameworks and model providers
• Memory - Memory strategies and sharing
• Local Development - Dev server and debugging

Feedback & Issues

Found a bug or have a feature request? Open an issue on GitHub.

Security

See SECURITY for reporting vulnerabilities and security information.

License

This project is licensed under the Apache-2.0 License.