Don’t give your AI agents raw data. Give them expertise.
Most MCP integrations hand your AI agent a data feed and leave it to figure out the rest. Kubex was purpose built for agentic operations: the intelligence and automation a small team needs to run large, dynamic environments.
- Deterministic ML at the core, so every optimization decision is predictable and explainable
- Purpose-built sub-agents keep every task focused, with no context drift
- Human-in-the-loop where you want it, autonomous where you don’t
- MCP-native: connect Claude, Cursor, GitHub Copilot, or any agentic workflow
MCP Integration
Connect your preferred AI agent or coding environment and make it an infrastructure optimization expert. The full Kubex intelligence stack, callable via MCP.
- ML models, workload pattern analysis, and contextualized recommendations your LLM can’t derive from raw metrics alone
- Specialized optimization agents for container sizing, predictive scaling, bin packing, node optimization, and GPU efficiency
- Agent-to-agent by design: Kubex works alongside your FinOps, SRE, and RCA tooling, with what-if analysis and simulations on demand
Conversational Interface
Ask Kubex anything about your infrastructure in plain language. Direct, explainable answers without digging through dashboards.
- Query resource behavior, changes, and optimization decisions in natural language
- Jump straight to any container, node, or event by asking
- Share findings with interactive tables and deep links
Deterministic AI
Every optimization decision is predictable, repeatable, and traceable to the policy and data that drove it. That’s what lets your team, and your AI agents, act on it at scale.
- Grounded in ML models of actual workload behavior, not LLM guesses
- Automation controller with admission mutation, in-place resizing, safety checks, dry runs, rollback, and audit trails
- Designed to earn trust gradually, not demand it upfront
Private LLM Integration
LLMs make Kubex easier to use. They never make the decisions. And we never train on your data.
- In-platform insights without exposing your data to external models
- LLMs explain and summarize; the deterministic engine decides
- Full audit trail on every AI interaction
How it all fits together
From your AI agent to the Kubex intelligence stack, down to every container and node.
Make your AI agents infrastructure experts.
Connect via MCP in minutes. Optimization intelligence your agents can trust, and act on.
SREs, Platform Owners and FinOps teams are succeeding and saving $millions.
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