Retrieve detailed AWS cost and usage data with individual resource-level granularity for EC2 instances, RDS databases, and S3 buckets to enable cost allocation, rightsizing analysis, and optimization opportunities.
The Unlicense
306,109 tools. Last updated 2026-07-25 02:11
"AWS Cost and Usage Analysis with Cost Optimization Recommendations" matching MCP tools:
- Retrieve and analyze AWS cost and usage data across services, accounts, and custom dimensions for cost optimization, budgeting, and financial reporting.The Unlicense
- Retrieve AWS cost optimization recommendations across 19 resource types to identify potential savings and improve cloud spending efficiency.MIT
- Retrieve detailed cost analysis for a cluster, including cost breakdown, resource utilization, node recommendations, and anomaly detection.Apache 2.0
- Analyze AWS RDS instances to identify cost-saving opportunities and optimization recommendations for database resources.MIT
- Analyze inference subscription usage patterns to identify optimization opportunities and potential cost savings for Vultr cloud infrastructure.MIT
Matching MCP Servers
- Alicense-qualityDmaintenanceEnables querying AWS Cost and Usage Report data via Amazon Athena for cost-effective and detailed cost analysis.Last updated1MIT
- Alicense-qualityBmaintenanceEnables scanning AWS accounts for cost optimization opportunities by reading resource configurations and pricing data, without making any modifications.Last updated22MIT
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- Analyze EC2 instances to identify cost-saving opportunities and provide optimization recommendations for reducing AWS expenses.MIT
- Analyze AWS Lambda functions to identify cost-saving opportunities and generate optimization recommendations for reducing cloud expenses.MIT
- Analyze AWS usage patterns to identify Reserved Instance purchase opportunities that reduce cloud costs. Provides data-driven recommendations from AWS Cost Explorer.MIT
- Generate AWS Savings Plans recommendations from Cost Explorer to optimize cloud spending and reduce costs.MIT
- Rank curated AI models by speed, cost, quality, or balanced priority. Get top 5 recommendations with cost estimates and reasoning to pick the right model for your task.MIT
- Check for unexpected cost spikes and billing anomalies with severity and impact ratings.MIT
- Execute a single AI model call to test prompts before building full workflows. Returns output, token usage, estimated provider cost, and trace URL.MIT
- Get prioritized actionable insights with estimated daily savings for cloud optimization across security, cost, and efficiency.MIT
- Get total spend, period-over-period trend, top resources by cost, and cost trend for a specific infrastructure diagram layer over a date range.MIT
- Analyzes AI spend by breaking down costs per developer and model, showing cost per million tokens and per message, with total cost and token usage rollups.MIT
- Retrieve daily LLM usage, cost trend, and model breakdown for a specific agent to optimize inference spending.MIT
- Retrieve LLM inference usage per agent with token consumption, GPU cost, and request counts. Pinpoint which agents and teams consume the most resources and cost.MIT
- Send text prompts or message arrays to LLMs like Claude or GPT, receiving responses with token usage and credit cost.MIT
- Retrieve your current-month MCP API usage, including metered calls, quota, overage calls, and projected overage cost. Monitor billing usage to avoid unexpected charges.MIT