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Analyze AWS costs, find waste, and recommend optimizations using read-only MCP tools
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Baseado na classificação ocupacional SOC
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| name | aws-cost-optimizer |
| description | Analyze AWS costs, find waste, and recommend optimizations using read-only MCP tools |
| version | 1.0.0 |
| author | kai-agent |
| metadata | {"kai":{"tags":["kai","aws","cost","optimization","finops"],"related_skills":["aws-performance"]}} |
Analyze AWS spending, identify waste, and recommend cost optimizations. All operations are read-only — no changes are made to infrastructure.
mcp__kai__aws_*Get a snapshot of current spending and trend.
Get last 30 days of costs:
aws_cost_summary(workspaceId, startDate="YYYY-MM-DD", endDate="YYYY-MM-DD")
Forecast next 30 days:
aws_cost_forecast(workspaceId, startDate="today", endDate="+30d", granularity="MONTHLY")
Present findings as a table:
| Service | Last 30d | Forecast | Trend |
|---|
Systematically identify unused/idle resources.
Unused EBS volumes (easy win):
aws_ec2_unused_volumes(workspaceId)
Each unattached volume costs money. Calculate: size_gb * $0.10/month
Unattached Elastic IPs:
aws_ec2_unattached_eips(workspaceId)
Each costs ~$3.65/month
Idle EC2 instances (biggest savings potential):
aws_ec2_list_instances(workspaceId, state="running")
Then for each instance, check CPU over 7 days:
aws_cloudwatch_get_metrics(
workspaceId, namespace="AWS/EC2", metricName="CPUUtilization",
dimensions=[{"name":"InstanceId","value":"i-xxx"}],
startTime="-7d", endTime="now", period=3600, statistics=["Average"]
)
Oversized Lambda functions:
aws_lambda_list_functions(workspaceId)
Then check actual duration vs configured memory:
aws_cloudwatch_get_metrics(
workspaceId, namespace="AWS/Lambda", metricName="Duration",
dimensions=[{"name":"FunctionName","value":"xxx"}],
startTime="-7d", endTime="now", period=86400, statistics=["Average","Maximum"]
)
Find gaps in Reserved Instances / Savings Plans.
RI coverage:
aws_reservation_coverage(workspaceId, startDate="-30d", endDate="today")
Savings Plans coverage:
aws_savings_plans_coverage(workspaceId, startDate="-30d", endDate="today")
List all buckets:
aws_s3_list_buckets(workspaceId)
Analyze each significant bucket:
aws_s3_bucket_analysis(workspaceId, bucketName="xxx")
Present findings as:
Current monthly spend: $X,XXX Estimated monthly savings: $XXX (X%)
| Finding | Service | Monthly Cost | Savings | Severity |
|---|---|---|---|---|
| 5 unused EBS volumes | EC2 | $50 | $50 | Low |
| 3 idle instances (CPU <5%) | EC2 | $450 | $300 | High |
| No lifecycle rules on logs bucket | S3 | $200 | $150 | Medium |
Recommendations (by impact):