Add AgentCore Gateway + Runtime setup steps (CLI-driven)

scripts/agentcore_setup.sh

@@ -0,0 +1,41 @@
+#!/usr/bin/env bash
+# AgentCore setup (steps 3-4-7). Terraform's AgentCore coverage lags, so this
+# stage uses the AgentCore CLI / SDK. Commands below reflect the current CLI
+# shape -- CHECK against `agentcore --help`, the surface moves fast.
+set -euo pipefail
+
+: "${REGION:?set REGION}"
+: "${RAG_LAMBDA_ARN:?set RAG_LAMBDA_ARN (from: terraform output -raw rag_lambda_arn)}"
+: "${BEDROCK_MODEL_ID:=anthropic.claude-3-5-sonnet-20241022-v2:0}"
+
+echo "==> 1. Install the AgentCore CLI (recommended tooling)"
+echo "    npm install -g @aws/agentcore    # or: pip install bedrock-agentcore-starter-toolkit"
+
+echo "==> 2. Create a Gateway that exposes the RAG Lambda as an MCP tool"
+echo "    AgentCore Gateway turns a Lambda into an MCP tool with no code changes."
+cat <<EOF
+    agentcore gateway create \\
+      --name hncb-rag-gateway \\
+      --region ${REGION} \\
+      --target-type lambda \\
+      --target-arn ${RAG_LAMBDA_ARN} \\
+      --tool-name get_customer_activity_summary \\
+      --tool-description "Return a de-identified activity summary for a customer TOKEN" \\
+      --tool-schema file://../agent/tool_schema.json
+    # Note the printed Gateway MCP URL -> export AGENTCORE_GATEWAY_URL=...
+EOF
+
+echo "==> 3. Deploy the agent to AgentCore Runtime"
+cat <<EOF
+    cd ../agent
+    agentcore configure --entrypoint agent.py --name hncb-advisor-agent --region ${REGION}
+    AGENTCORE_GATEWAY_URL=<from step 2> BEDROCK_MODEL_ID=${BEDROCK_MODEL_ID} \\
+      agentcore launch
+    # Note the printed Runtime ARN -> Fusion will invoke this.
+EOF
+
+echo "==> 4. (recommended) Lock the Runtime to accept calls only from the Gateway"
+echo "    Use a resource policy (SigV4) or allowedWorkloadConfiguration (JWT)."
+echo "    See AgentCore 'Runtime targets' docs."
+
+echo "Done printing steps. Fill AGENTCORE_GATEWAY_URL + Runtime ARN into fusion/POLICY_SETUP.md."