aws/agentcore-cli

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# AgentCore CLI `agentcore` is a command-line tool and interactive terminal UI (TUI) for **[Amazon Bedrock AgentCore](https://aws.amazon.com/bedrock/agentcore/)**, the platform for building and running production AI agents ([documentation](https://docs.aws.amazon.com/bedrock-agentcore/)). It gives you two ways to work, from the same package: - **A scriptable CLI** — flag-driven commands with JSON output (`--json`) for coding agents, scripts, and CI. - **An interactive TUI** — guided flows for creating projects, browsing resources, and chatting with agents. ```bash agentcore # launch the interactive TUI agentcore status --json # scriptable, machine-readable output ``` Using the AgentCore APIs directly means calling several services, setting up execution roles, and handling streamed responses. `agentcore` takes care of those details so you can create, deploy, and invoke agents from your terminal. ## Installation You need Node.js 20.12 or later and AWS credentials configured as for the AWS CLI. Python templates also need [`uv`](https://docs.astral.sh/uv/getting-started/installation/). ```bash npm install -g @aws/agentcore ``` If the Python-based Bedrock AgentCore Starter Toolkit is installed, uninstall it: both provide an `agentcore` command. ## Quick Start A project holds either kind of agent, or both: - A **Harness** is a managed agent you configure in YAML — model, system prompt, tools, skills — and AgentCore runs for you. - A **Runtime** is agent code you own, scaffolded from a template and deployed for you. Create a project, add a Harness to it, deploy it, and send a prompt: ```bash agentcore create --name MyProject cd MyProject agentcore add harness --name MyAssistant agentcore deploy agentcore invoke --harness MyAssistant --prompt "Hey, what can you do for me?" ``` To invoke a CUSTOM_JWT Harness, supply AWS credentials for the Harness lookup and pipe a bearer token for the invocation: ```bash printf '%s' "$JWT" | agentcore invoke \ --harness MyAssistant-AbCdEf1234 \ --region us-east-1 --bearer-token - --prompt "Hello" ``` The same flags work with `agentcore harness invoke --id <harness-id>`. You can also select a Harness by ARN with `agentcore invoke --harness <harness-arn>`, but the CLI still looks up its configuration before invoking it. `--bearer-token file://<path>` reads a token from a file. To start from code you own instead, pick a template (`agentcore create --help` lists them): ```bash agentcore create --name MyAgent --template agent-python-strands ``` `agentcore create --template` scaffolds the template with its default model provider (Amazon Bedrock for the model-backed templates). To use another provider, run `agentcore create` with no flags: for templates that take a model provider (`agent-python-strands` and its `-container` variant, `a2a-python-strands`, `agui-python-strands`, `agent-typescript-strands`) the wizard asks for the provider (Amazon Bedrock, Anthropic, OpenAI, an OpenAI-compatible endpoint, Gemini, or LiteLLM, which is Python-only), the model id, and an API-key file. The API key is kept in `agentcore/.env.local` and provisioned as an AgentCore Identity credential on deploy. To bring your own code into a project instead, add a runtime for it: ```bash agentcore add runtime --name search --language python # or --language typescript ``` `add runtime` doesn't generate code. It creates `app/search/` with a `README.md` and an `AGENTS.md` describing what the code has to provide for the chosen `--protocol` (`HTTP` by default, or `MCP`, `A2A`, `AGUI`), and registers the runtime in `agentcore.json` with starting values (a CodeZip build on the latest Python or Node.js, entrypoint `main.py` or `main.js`). If `app/search/` already exists, your files are left alone and only the missing docs are added. `agentcore dev`, `agentcore build`, and `agentcore deploy` then update `agentcore.json` from the code and print what changed. Adding a `Dockerfile` to the folder switches the runtime to a container build. `requires-python` in `pyproject.toml` or `engines.node` in `package.json` constrains the runtime version: it changes only when the range excludes the current one, and then to the highest version the range allows. The Python entrypoint comes from `[tool.agentcore] entrypoint` in `pyproject.toml`; TypeScript is always bundled from `main.ts` (a `package.json` `"main"` of `main.ts` or `main.js` agrees with that, and any other value is ignored with a warning). Where the code doesn't say, the value in `agentcore.json` is kept. Run `agentcore create` outside any existing project. ## Projects `create` makes a directory holding `agentcore/agentcore.json`, the spec that declares the project's resources, and `agentcore/cdk/`, the AWS CDK app that deploys them. Deployment targets — an account and region each — live in `agentcore/aws-targets.json`. Project commands find the project by walking up from the current directory. `agentcore dev` runs runtimes locally or deploys harnesses and prints invoke guidance. Use `--mode browser` for Agent Inspector, `--skip-deploy` to reuse deployed harnesses, and `--agent <name>` to choose an agent in mixed projects. New payment credentials receive provider names that payment connectors can reference. An existing payment credential keeps the provider ARN recorded for its deployment target. If that ARN is incompatible with a manual connector, deploy stops before provisioning anything. Add a payment credential under a different name and point the connector to it; the old provider remains until you remove its credential from the project and deploy each affected target. ## Commands | Command | Purpose | | ---------------------------------------------------------------- | ---------------------------------------------------------------------------------------------- | | `create`, `add`, `remove`, `export`, `migrate` | Create a project, add or remove its resources, export a resource to code, migrate a v0 project | | `dev`, `build`, `deploy`, `status` | Run locally, build, deploy, and check what is deployed | | `invoke`, `logs`, `traces` | Talk to deployed agents and inspect their logs and traces | | `runtime`, `harness`, `gateway`, `memory`, `identity`, `payment` | Inspect and manage deployed resources, with or without a project | | `eval` | Evaluate agents, manage datasets and configurations, and run experiments | | `feedback`, `config`, `update` | Send feedback, read and write CLI settings, update the CLI | In a terminal, a command run without flags opens its interactive flow; pass flags and it runs non-interactively. `--help` on any command lists its subcommands and flags, and the [command reference](command.md) has them all. Global flags, available on every command: | Flag | Purpose | | ---------- | ------------------------------------------------------------------------------------------------------------------- | | `--region` | AWS region. Resolved from this flag, then `AWS_REGION`, `AWS_DEFAULT_REGION`, the active profile, then `us-east-1`. | | `--json` | Emit JSON instead of opening the TUI. | | `--debug` | Debug logging. | ## Extending the CDK app `agentcore/cdk/` has two source files. `bin/cdk.ts` reads the project once (`readAgentCoreProject`), makes one stack per deployment target (`resolveTargetStacks`) and turns `agentcore.json` into the application's props (`transformAgentCoreJson`). All three come from `@aws/agentcore-cdk`, so that logic is updated through the library rather than changes to your CDK app. `lib/cdk-stack.ts` instantiates one `AgentCoreApplication`. This is the file you edit to add your own resources. Runtimes and harnesses implement `iam.IGrantable`, so you can pass them to a resource's CDK grant methods to give your agents access. Use `addEnvironmentVariable` to pass resource names, ARNs, or endpoints to your agent. This example gives the generated runtime named `agent` access to a table: ```ts import { AgentCoreApplication, type AgentCoreApplicationProps } from "@aws/agentcore-cdk"; import { Stack, type StackProps } from "aws-cdk-lib"; import * as dynamodb from "aws-cdk-lib/aws-dynamodb"; import { Construct } from "constructs"; export interface AgentCoreStackProps extends StackProps { application: AgentCoreApplicationProps; } export class AgentCoreStack extends Stack { public readonly application: AgentCoreApplication; constructor(scope: Construct, id: string, props: AgentCoreStackProps) { super(scope, id, props); this.application = new AgentCoreApplication(this, "Application", props.application); const orders = new dynamodb.Table(this, "Orders", { partitionKey: { name: "pk", type: dynamodb.AttributeType.STRING }, }); const agent = this.application.runtime("agent"); orders.grantReadWriteData(agent); agent.addEnvironmentVariable("ORDERS_TABLE", orders.tableName); } } ``` For a Harness, use `this.application.harness("<name>")` instead. Run `agentcore deploy` to apply your changes. The names passed to `runtime()` or `harness()` must match the names in your project. If you use an existing execution role through `executionRoleArn`, CDK cannot change its permissions. You'll need to add the required permissions to that role yourself. Note that `agentcore status` reports only the resources `agentcore.json` declares, not the ones you add in the stack. ## Documentation - [Command reference](command.md): every command and flag. - [Harness project configuration](docs/harness-project-configuration.md): Harness YAML, prompts, tools, skills, and environment settings. - [China regions](docs/china-regions.md): what is available there and how the restrictions are enforced. - [Amazon Bedrock AgentCore documentation](https://docs.aws.amazon.com/bedrock-agentcore/): service guides and API references. - [Contributing](CONTRIBUTING.md): development, builds, architecture, and testing. - [Security](SECURITY.md) · [License](LICENSE): Apache-2.0.

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Save a report of the Python version, user ID, and working directory of the ACR in the workspace.

原文语言：英语

2026-09-30

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