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CopilotKit + AWS AgentCore

examples/integrations/agentcore/README.md

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CopilotKit + AWS AgentCore

Chat UI with generative charts, shared-state todo canvas, and inline tool rendering — deployed on AWS Bedrock AgentCore. Pick LangGraph or Strands.

Prerequisites

ToolVersion
AWS CLIconfigured (aws configure)
Node.js18+
uvany recent release
Dockerrunning

The Python side is managed entirely by uv — it provisions the interpreter, so there is no separate Python install step.

Managed Intelligence credentials

Create the root environment file before deploying or running locally:

bash
cp .env.example .env

Set CPK_INTELLIGENCE_API_KEY to the API key for your managed CopilotKit Intelligence project. CPK_TELEMETRY_ID is an optional, non-secret analytics identity and can stay blank.

Deploy to AWS

  1. Create your environment and config:

    bash
    cp .env.example .env
    cp config.yaml.example config.yaml
    # Edit .env and config.yaml.
    

    Set stack_name_base and admin_user_email in config.yaml. The deploy script stores the managed key from .env in its configured AWS Secrets Manager secret. CDK resolves it only for the CopilotKit runtime Lambda.

    Managed Intelligence uses its default endpoints. For self-hosted Intelligence, set endpoint overrides that AWS can reach. Do not use localhost, 127.0.0.1, or the Docker-only host.docker.internal name from .env.example.

  2. Deploy:

    bash
    ./deploy-langgraph.sh                    # LangGraph agent (infra + frontend)
    ./deploy-langgraph.sh --skip-frontend    # infra/agent only
    ./deploy-langgraph.sh --skip-backend     # frontend only
    # or
    ./deploy-strands.sh                      # AWS Strands agent
    ./deploy-strands.sh --skip-frontend
    ./deploy-strands.sh --skip-backend
    
    # Self-hosted Intelligence only:
    INTELLIGENCE_API_URL=https://intelligence.example.com \
    INTELLIGENCE_GATEWAY_WS_URL=wss://gateway.example.com \
    ./deploy-langgraph.sh
    INTELLIGENCE_API_URL=https://intelligence.example.com \
    INTELLIGENCE_GATEWAY_WS_URL=wss://gateway.example.com \
    ./deploy-strands.sh
    

    The command-prefixed endpoint values override the managed defaults. Use the same prefix with --skip-frontend or --skip-backend when needed.

  3. Open the Amplify URL printed at the end. Sign in with your email.

Local Development

bash
cp .env.example .env
cp docker/.env.example docker/.env
cd docker
# Fill in docker/.env AWS creds — STACK_NAME, MEMORY_ID, and aws-exports.json are auto-resolved
# For local Intelligence, uncomment the host.docker.internal URLs in ../.env.
./up.sh --build
  • Frontend → hot reloads on save (volume mount + Vite)
  • Agent → rebuild on changes: docker compose up --build agent
  • Browserhttp://localhost:3000, auth redirects back to localhost

The full chain runs locally: browser:3000 → bridge:3001 → agent:8080. AWS is only used for Memory and Gateway (SSM/OAuth2).

Agent dependencies

Each single-agent directory under agents/langgraph-single-agent/ and strands-single-agent/ — is its own uv project with its own uv.lock, and the Dockerfiles install with uv sync --locked — so the image gets exactly the dependency set in the lockfile, not whatever resolves that day. agents/utils/ is the exception: it is shared source that both Dockerfiles COPY in, not a project, so it has no pyproject.toml or lockfile of its own and anything it imports must be declared in each agent that copies it.

bash
cd agents/langgraph-single-agent
uv add some-package        # or edit pyproject.toml, then: uv lock

Either way, commit the updated uv.lock alongside pyproject.toml. Terraform hashes both, so a dependency change retriggers the image build on the next apply.

What's inside

PieceWhat it does
frontend/Vite + React with CopilotKit chat, charts, todo canvas
agents/langgraph-single-agent/LangGraph agent with tools + shared todo state
agents/strands-single-agent/Strands agent with tools + shared todo state
pyproject.toml / uv.lockDependencies for the scripts/ helpers
infra-cdk/CDK: Cognito, AgentCore, CopilotKit Lambda bridge, Amplify
infra-terraform/Base AgentCore infrastructure without managed Intelligence
docker/Local dev via Docker Compose

Architecture

Browser → API Gateway → CopilotKit Lambda (Node.js, AG-UI bridge)
                              ↓
                        AgentCore Runtime
                              ↓
                    langgraph_agent.py / strands_agent.py
                              ↓ MCP (OAuth2 M2M)
                        AgentCore Gateway → Lambda tools

Auth: Cognito OIDC → Bearer token forwarded from browser through Lambda to AgentCore.

Tear down

bash
cd infra-cdk && npx cdk@latest destroy --all --output ../cdk.out-lg   # LangGraph stack
cd infra-cdk && npx cdk@latest destroy --all --output ../cdk.out-st   # Strands stack

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