diff --git a/local-app/python-tools/billing/aws_monthly_cost.py b/local-app/python-tools/billing/aws_monthly_cost.py
new file mode 100755
index 00000000..6d80a32a
--- /dev/null
+++ b/local-app/python-tools/billing/aws_monthly_cost.py
@@ -0,0 +1,80 @@
+#!/bin/env python
+
+import boto3
+import csv
+import datetime
+from botocore.exceptions import ClientError
+
+def get_monthly_range(target_date=None):
+    """Calculates the start of the current month and the start of the next month."""
+    if target_date is None:
+        target_date = datetime.date.today()
+    
+    # Start of target month
+    start = target_date.replace(day=1)
+    
+    # Start of next month (End date is exclusive in AWS API)
+    if start.month == 12:
+        end = start.replace(year=start.year + 1, month=1)
+    else:
+        end = start.replace(month=start.month + 1)
+        
+    return start.strftime('%Y-%m-%d'), end.strftime('%Y-%m-%d')
+
+def fetch_aws_costs():
+    client = boto3.client('ce', region_name='us-east-1') # CE API is us-east-1 only
+    start_date, end_date = get_monthly_range()
+    
+    print(f"Fetching costs from {start_date} to {end_date}...")
+
+    try:
+        response = client.get_cost_and_usage(
+            TimePeriod={'Start': start_date, 'End': end_date},
+            Granularity='MONTHLY',
+            Metrics=['BlendedCost', 'UnblendedCost', 'AmortizedCost', 'UsageQuantity'],
+            GroupBy=[{'Type': 'DIMENSION', 'Key': 'SERVICE'}]
+        )
+
+        rows = []
+        grand_totals = {'blended': 0.0, 'unblended': 0.0, 'amortized': 0.0}
+
+        for group in response['ResultsByTime'][0]['Groups']:
+            service_name = group['Keys'][0]
+            metrics = group['Metrics']
+            
+            # Extracting values
+            usage_qty = float(metrics['UsageQuantity']['Amount'])
+            usage_unit = metrics['UsageQuantity']['Unit']
+            blended = float(metrics['BlendedCost']['Amount'])
+            unblended = float(metrics['UnblendedCost']['Amount'])
+            amortized = float(metrics['AmortizedCost']['Amount'])
+
+            rows.append([service_name, f"{usage_qty:.2f}", usage_unit, f"{blended:.2f}", f"{unblended:.2f}", f"{amortized:.2f}"])
+            
+            # Update Grand Totals
+            grand_totals['blended'] += blended
+            grand_totals['unblended'] += unblended
+            grand_totals['amortized'] += amortized
+
+        # Sorting by cost (Amortized/Total) descending
+        rows.sort(key=lambda x: float(x[5]), reverse=True)
+
+        # Write to CSV
+        filename = f"aws_cost_{start_date[:7]}.csv"
+        with open(filename, 'w', newline='') as f:
+            writer = csv.writer(f)
+            writer.writerow(['Service', 'Usage Quantity', 'Unit', 'Blended Cost', 'Unblended Cost', 'Total (Amortized)'])
+            writer.writerows(rows)
+            # Grand Total Line
+            writer.writerow(['GRAND TOTAL', 'NA', 'NA', 
+                             f"{grand_totals['blended']:.2f}", 
+                             f"{grand_totals['unblended']:.2f}", 
+                             f"{grand_totals['amortized']:.2f}"])
+
+        print(f"✅ Success! Report saved as {filename}")
+
+    except ClientError as e:
+        print(f"❌ Error: {e}")
+
+if __name__ == "__main__":
+    fetch_aws_costs()