--- name: deploy-agentcore description: Deploy Python agents to AWS Bedrock AgentCore. Use when deploying agents to AWS, setting up serverless agent hosting, configuring AgentCore components (Runtime, Gateway, Memory, Identity, Policy), or troubleshooting deployment errors. --- AWS Bedrock AgentCore is a serverless platform for AI agents at scale. ## Architecture AgentCore has 6 modular components: - **Runtime** - Serverless hosting (direct_code_deploy or container) - **Gateway** - Tool access via MCP (Lambda, OpenAPI, Smithy targets) - **Memory** - STM (session) and LTM (persistent) storage - **Identity** - Auth via IAM, Cognito, AWS JWT, external OAuth - **Observability** - CloudWatch + OpenTelemetry tracing - **Policy** - Cedar-based governance and authorization ## Entry Point Pattern All agents use `BedrockAgentCoreApp` with `@app.entrypoint` decorator: ```python from bedrock_agentcore import BedrockAgentCoreApp app = BedrockAgentCoreApp() @app.entrypoint def invoke(payload: dict) -> dict: prompt = payload.get("prompt", "") result = your_agent_logic(prompt) return {"result": result} if __name__ == "__main__": app.run() ``` ## Key CLI Commands All commands: `uv run agentcore [command]` Runtime: configure, deploy, invoke, status, destroy, stop-session Gateway: gateway create-mcp-gateway, gateway create-mcp-gateway-target Memory: memory create, memory list, memory status Identity: identity setup-cognito, identity setup-aws-jwt Policy: policy create-policy-engine, policy create-policy See references\/cli-reference.md for full command list. ## Rules - Agent names: underscores only (`my_agent` not `my-agent`) - Never hardcode API keys - use Secrets Manager - Windows: prefix with `PYTHONIOENCODING=utf-8` - Memory mode order: `STM_AND_LTM` (not LTM_AND_STM) <\/essential_principles> What would you like to do? 1. Deploy a new agent 2. Update existing deployment 3. Add Google OAuth 4. Create chat UI 5. Set up Gateway (MCP tools) 6. Configure Memory 7. Set up Identity\/Auth 8. View logs\/observability 9. Troubleshoot errors 10. Something else Wait for response before proceeding. <\/intake> | Response | Workflow | |----------|----------| | 1, "deploy", "new" | workflows\/deploy-agent.md | | 2, "update", "redeploy" | workflows\/update-deployment.md | | 3, "oauth", "google" | workflows\/add-oauth.md | | 4, "ui", "chat", "streamlit" | workflows\/create-chat-ui.md | | 5, "gateway", "mcp", "tools" | workflows\/setup-gateway.md | | 6, "memory", "stm", "ltm" | workflows\/setup-memory.md | | 7, "identity", "auth", "cognito", "jwt" | workflows\/setup-identity.md | | 8, "logs", "observability", "cloudwatch" | workflows\/view-logs.md | | 9, "error", "troubleshoot", "fix" | workflows\/troubleshoot.md | | 10, other | Clarify, then select | After reading the workflow, follow it exactly. <\/routing> All domain knowledge in `references\/`: - architecture.md - All AgentCore components explained - cli-reference.md - Complete CLI command reference - prerequisites.md - AWS setup, Python, uv requirements - memory-modes.md - Memory configuration details - common-errors.md - Error messages and fixes - iam-policies.md - IAM role configuration <\/reference_index> | Workflow | Purpose | |----------|---------| | deploy-agent.md | Deploy Python agent to AgentCore | | update-deployment.md | Redeploy with code changes | | add-oauth.md | Add Google OAuth for cloud environment | | create-chat-ui.md | Create Streamlit chat interface | | setup-gateway.md | Create MCP gateway with targets | | setup-memory.md | Configure memory modes | | setup-identity.md | Set up auth (Cognito, JWT, OAuth) | | view-logs.md | Access CloudWatch logs and metrics | | troubleshoot.md | Fix common deployment errors | <\/workflows_index> | Template | Purpose | |----------|---------| | entry_claude_sdk.py | Entry point for Claude SDK agents | | entry_langchain.py | Entry point for LangChain agents | | entry_custom.py | Entry point for custom Python agents | | entry_minimal.py | Bare minimum entry point | | policy_minimal.json | IAM policy for Secrets Manager only | | policy_oauth.json | IAM policy for OAuth (Secrets + S3) | | policy_full.json | IAM policy with all common permissions | | chat_ui.py | Streamlit chat interface | <\/templates_index> Deployment successful when: - `uv run agentcore deploy` completes without errors - `uv run agentcore invoke` returns expected response - Agent handles sessions correctly - External API keys work via Secrets Manager <\/success_criteria>