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‎docs/snippets/integrations/agentcore/full-stack-example.mdx‎

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## Prerequisites
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| Tool | Version |
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|---|---|
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| AWS CLI | configured (`aws configure`) |
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| Node.js | 18+ |
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| Python | 3.8+ |
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| Docker | running |
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- **AWS CLI** — configured (`aws configure`)
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- **Node.js** 18+
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- **Python** 3.8+
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- **Docker** — running
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## Deploy
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**1. Clone the example**
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```bash
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git clone https://github.com/CopilotKit/CopilotKit.git
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cd CopilotKit/examples/integrations/agentcore
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```
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**2. Configure**
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```bash
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cp config.yaml.example config.yaml
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```
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Edit `config.yaml` and set `stack_name_base` (a short prefix for your AWS resources) and
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`admin_user_email` (where your Cognito invite will be sent).
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The CLI scaffolds the project, sets up your config, and a single script deploys the full stack — CDK infrastructure, AgentCore Runtime, and the frontend — in one shot.
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**3. Deploy**
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<Steps>
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<Step>
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### Scaffold the project
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<Tabs groupId="agent-framework" items={["LangGraph", "Strands"]}>
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<Tab value="LangGraph">
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```bash
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./deploy-langgraph.sh
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```
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</Tab>
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<Tab value="Strands">
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```bash
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./deploy-strands.sh
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npx copilotkit@latest create -f agentcore-langgraph
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# or
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npx copilotkit@latest create -f agentcore-strands
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```
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</Tab>
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</Tabs>
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</Step>
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The script deploys the full CDK stack and prints an Amplify URL when done. Sign in with your
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`admin_user_email`.
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<Step>
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### Configure
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<Callout type="info" title="Prefer Terraform?">
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A Terraform equivalent is available in `infra-terraform/`. See `infra-terraform/README.md` for
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setup and deploy steps.
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</Callout>
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```bash
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cp config.yaml.example config.yaml
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```
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<Callout type="info" title="Infra only">
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Pass `--skip-frontend` to deploy or update the agent and infrastructure without rebuilding
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the frontend:
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```bash
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./deploy-langgraph.sh --skip-frontend
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```
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</Callout>
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Edit `config.yaml` and set `stack_name_base` (a short prefix for your AWS resources) and
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`admin_user_email` (where your Cognito invite will be sent).
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</Step>
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<Step>
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### Deploy
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<Tabs groupId="agent-framework" items={["LangGraph", "Strands"]}>
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<Tab value="LangGraph">
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```bash
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./deploy-langgraph.sh
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```
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</Tab>
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<Tab value="Strands">
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```bash
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./deploy-strands.sh
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```
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</Tab>
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</Tabs>
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The script deploys the full CDK stack and prints an Amplify URL when done. Sign in with your
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`admin_user_email`.
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<Callout type="info" title="Prefer Terraform?">
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A Terraform equivalent is available in `infra-terraform/`. See `infra-terraform/README.md` for
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setup and deploy steps.
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</Callout>
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<Callout type="info" title="Infra only">
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Pass `--skip-frontend` to deploy or update the agent and infrastructure without rebuilding
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the frontend:
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```bash
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./deploy-langgraph.sh --skip-frontend
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```
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</Callout>
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</Step>
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</Steps>
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## Local development
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it to AgentCore, which validates it and makes the `sub` claim available to the agent as the
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user identity.
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## Generative UI
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The agent renders charts and UI components directly in the chat by calling frontend tools.
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The frontend registers these tools with `useCopilotAction`:
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```tsx
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useCopilotAction({
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name: "barChart",
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parameters: [
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{ name: "data", type: "object[]" },
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{ name: "title", type: "string" },
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],
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render: ({ data, title }) => <BarChart data={data} title={title} />,
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});
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```
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The agent calls `barChart` with data (fetched first via `query_data`), and the chart
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appears inline in the chat — no extra user interaction needed.
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## Shared state
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The todo canvas demonstrates bidirectional state sync between the agent and the frontend.
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The agent maintains a `todos` list in its state; the frontend reads and writes it in real time.
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**Agent side** (LangGraph):
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```python
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class AgentState(BaseAgentState):
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todos: list[Todo]
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@tool
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def manage_todos(todos: list[Todo], runtime: ToolRuntime) -> Command:
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"""Replace the entire todo list."""
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return Command(update={"todos": todos, "messages": [...]})
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```
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**Frontend side:**
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```tsx
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const { agent } = useAgent();
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// Read agent state
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const todos = agent.state?.todos ?? [];
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// Write agent state (user interaction)
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agent.setState({ todos: updatedTodos });
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```
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The agent calls `manage_todos` to update todos; the UI reacts instantly. Users can also
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edit todos directly and those changes flow back to the agent's state.
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## Tear down
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When you're done experimenting, run this to delete all AWS resources created by the deployment — the AgentCore Runtime, Cognito user pool, Lambda, API Gateway, and Amplify app. This stops any ongoing AWS charges.
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```bash
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cd infra-cdk && npx cdk destroy --all
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```

‎docs/snippets/integrations/agentcore/index.mdx‎

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[AWS Bedrock AgentCore](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/what-is-bedrock-agentcore.html)
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gives you a secure, serverless runtime for deploying AG-UI agents at scale — handling auth, session
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isolation, and infrastructure. CopilotKit gives those agents a production-ready frontend: chat UI,
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shared state, generative UI, human-in-the-loop, and more.
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isolation, and infrastructure. CopilotKit gives those agents a production-ready frontend:
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**Chat UI** · **Shared State** · **Generative UI** · **Human-in-the-loop**
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## How it works
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The two connect through **CopilotKit Runtime**, a lightweight server-side layer that sits between
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your browser and AgentCore. It's the same runtime you'd use with any CopilotKit-powered agent —
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</div>
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</a>
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</div>
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## Prerequisites
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Before you begin, you should have:
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- An AG-UI agent deployed to [AgentCore Runtime](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/runtime-agui.html)
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- Your AgentCore endpoint URL (the `/invocations` URL returned after deployment)
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- A Cognito user pool set up for authentication (the AWS guide covers this)
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- Node.js 18+

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