AI for FinOps: Curated collection of MCP servers and resources for Cloud FinOps practitioners
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ecos is an open FinOps data stack with a CLI and MCP server that turns raw cloud data into actionable insights.
SDK to track cost-per-outcome for AI workflows
Cost effective data pipelines code repository
Free client-side cloud cost allocation readiness auditor — your CSV never leaves the browser
Tool that allows you to delete and stop resources across different clouds
Cloud/DevOps Engineer's best practices to save costs on cloud infrastructure
Developed a cloud cost optimization solution using Azure Monitor and AWS CloudWatch to track resource usage and implement cost-saving measures. The project automates scaling and alerts to ensure efficient cloud infrastructure management.
Regression-driven FinOps module for ShieldCraft AI. Predicts future compute spend with RMSE monitoring (≤4.7% target) and automates budget enforcement using Step Functions to optimize infrastructure cost reduction.
Go + React/Vite dashboard that polls ClusterCost agents to show real-time Kubernetes cost and resource insights, packaged for local run, Docker, and K8s deploys.
Optimisely.ai is set of tools for cloud cost optimisation and security improvements
Helm charts for Project Helena — open-source Kubernetes cost visibility and monitoring.
Python CLI tool to analyze AWS resources and identify cost optimization opportunities. Detects idle EC2 instances, unattached EBS volumes, outdated snapshots, unused Elastic IPs, and idle RDS databases with multi-format reporting.
ClusterCost’s Kubernetes agent that scrapes cluster objects/metrics and serves real-time hourly cost estimates via Prometheus metrics and a JSON API.
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