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
agentcorecommand 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/agentcoreUse 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
| Framework | Notes |
|---|---|
| Strands Agents | AWS-native, streaming support |
| LangChain/LangGraph | Graph-based workflows |
| Google ADK | Gemini models only |
| OpenAI Agents | OpenAI models only |
| Provider | API Key Required | Default Model |
|---|---|---|
| Amazon Bedrock | No (uses AWS credentials) | us.anthropic.claude-sonnet-4-5-20250514-v1:0 |
| Anthropic | Yes | claude-sonnet-4-5-20250514 |
| Google Gemini | Yes | gemini-2.5-flash |
| OpenAI | Yes | gpt-4.1 |
| Command | Description |
|---|---|
create | Create a new AgentCore project |
dev | Start local development server |
deploy | Deploy infrastructure to AWS |
invoke | Invoke deployed agents |
| Command | Description |
|---|---|
add | Add agents, memory, credentials, evaluators, targets |
remove | Remove resources from project |
Note: Run
agentcore deployafteraddorremoveto update resources in AWS.
| Command | Description |
|---|---|
logs | Stream or search agent runtime logs |
traces list | List recent traces for a deployed agent |
traces get | Download a trace to a JSON file |
status | Show deployed resource details |
| Command | Description |
|---|---|
add evaluator | Add a custom LLM-as-a-Judge evaluator |
add online-eval | Add continuous evaluation for live traffic |
run eval | Run on-demand evaluation against agent traces |
run batch-evaluation | Run evaluators across all sessions [preview] |
run recommendation | Optimize prompts and tool descriptions [preview] |
evals history | View past eval run results |
pause online-eval | Pause a deployed online eval config |
resume online-eval | Resume a paused online eval config |
stop batch-evaluation | Stop a running batch evaluation [preview] |
logs evals | Stream or search online eval logs |
| Command | Description |
|---|---|
add config-bundle | Add a versioned configuration bundle |
cb versions | List version history for a bundle |
cb diff | Diff two versions of a bundle |
cb create-branch | Create a new branch on an existing bundle |
Create agents with
--with-config-bundleto auto-wire config bundle support into the generated template.
| Command | Description |
|---|---|
validate | Validate configuration files |
package | Package agent artifacts without deploying |
fetch access | Fetch access info for deployed resources |
update | Check for and install CLI updates |
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 evalsdeployed-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
Found a bug or have a feature request? Open an issue on GitHub.
See SECURITY for reporting vulnerabilities and security information.
This project is licensed under the Apache-2.0 License.