Openops

OpenOps is a no‑code FinOps automation platform that tackles the perennial problem of cloud cost leakage and fragmented financial governance. By unifying visibility, decision‑making, and execution into a single workflow engine, it removes the need for custom scripting or disparate toolchains. Developers and FinOps teams can focus on high‑value analysis instead of plumbing together APIs, writing cron jobs, or maintaining manual spreadsheets.

At its core, OpenOps exposes a set of reusable workflows—each a chain of cloud‑provider calls, database queries, and notification steps—that can be dropped into any AI assistant via the MCP interface. These workflows cover everything from allocation and unit economics to anomaly detection, workload optimization, and safe de‑provisioning. Because the platform is built around a visual editor, a non‑technical stakeholder can modify a workflow in minutes, while engineers can “drop into” code for advanced customizations. The result is a living playbook that adapts to changing business rules without the overhead of traditional DevOps pipelines.

Key capabilities include a native OpenOps Tables database that acts like an Excel‑style data store, and OpenOps Analytics, a lightweight visualization layer for quick insights. Deep integrations with AWS, Azure, Google Cloud, and popular FinOps tools mean that the platform can pull cost data from anywhere in the stack. Human‑in‑the‑loop controls are woven throughout, allowing approvals to surface on Slack, Teams, or email before any resource is altered. Versioning and audit logs give full traceability, so teams can roll back or audit changes with confidence.

Real‑world use cases span the entire FinOps lifecycle. A cloud‑native startup can automate tagging and cost allocation across multiple environments, while a large enterprise can set up anomaly alerts that trigger instant remediation workflows. Project managers can surface cost‑saving opportunities directly in their task boards, and finance leaders can generate quarterly reports from the same data source that powers daily optimizations. By embedding OpenOps into an AI assistant’s MCP server, developers can trigger cost‑optimization actions with natural language commands—“Reduce idle RDS instances by 30%” or “Show me the top 5 cost anomalies for this month”—and let the assistant handle the orchestration.

OpenOps stands out because it merges automation, collaboration, and transparency into a single, cloud‑native package. Its no‑code interface lowers the barrier to entry for non‑technical users, while its MCP‑ready architecture ensures that developers can extend or embed the platform in any AI workflow. The result is a scalable, maintainable solution that turns cost‑optimization from an afterthought into a repeatable business process.