About this project
HelmsMan is an autonomous Kubernetes remediation platform built using the Model Context Protocol (MCP) and the NitroStack MCP SDK. It enables AI agents to safely analyze, reason about, and optimize a live Kubernetes cluster while ensuring that every infrastructure change complies with Kubernetes availability policies. Traditional autoscaling mechanisms rely mainly on CPU or memory thresholds and cannot determine whether a scaling operation is operationally safe, often leading to over-provisioned clusters, increased cloud costs, or actions that risk application downtime. HelmsMan addresses this limitation through a multi-agent architecture consisting of a FinOps Agent, which identifies cost-saving opportunities by detecting idle or over-provisioned workloads, and an Availability Guardian, which evaluates the potential impact of every proposed action on application reliability. Instead of allowing AI agents to directly execute changes, all remediation requests are routed through a deterministic Safety Engine that validates them against the live Kubernetes API by checking deployment health, replica counts, PodDisruptionBudget (PDB) constraints, and other availability requirements before any operation is performed. Unsafe actions are automatically rejected, while approved actions are executed and recorded in a comprehensive audit trail for complete transparency. The MCP server exposes Kubernetes functionality through standardized Tools, Resources, and Prompts, allowing AI systems to inspect cluster state, retrieve health information, and perform safe remediation using a common interface. By combining AI-driven decision-making with deterministic policy enforcement, HelmsMan transforms Kubernetes operations from reactive monitoring into intelligent, policy-aware automation that reduces operational effort, optimizes infrastructure costs, and maintains high application availability.
Open Innovation track
Solve any real-world problem with AI, regardless of industry or domain.