kagent

Deploy and manage AI agents on Kubernetes using CRDs.

27|11|Updated Dec 21, 2025

Search Tags:#ai #agents #kubernetes #crd #ops

Ready to run

npx skills add https://github.com/mjunaidca/mjs-agent-skills --skill kagent

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: kagent
Source: https://github.com/mjunaidca/mjs-agent-skills/tree/main/.docs/taskflow-vault/skills/engineering/kagent
Command: npx skills add https://github.com/mjunaidca/mjs-agent-skills --skill kagent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Provides a Kubernetes-native framework to build, deploy, and manage AI agents with CRD-driven lifecycle.

Core Features & Use Cases

Define AI agents as Kubernetes CRDs
AI-powered cluster health analysis and optimization
Extensibility with tooling and observability

Quick Start

Install CRDs, deploy the controller, and start defining Agent CRs to automate tasks.

Frequently Asked Questions about kagent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I deploy AI agents on Kubernetes using CRDs?▼

Deploying AI agents on Kubernetes uses Custom Resource Definitions to define agents declaratively. Install the CRDs, deploy the controller, then create Agent resources to automate cluster operations with AI-powered decision-making and lifecycle management.

What can AI agents automate in Kubernetes cluster operations?▼

AI agents automate complex Kubernetes operations including health analysis, resource optimization, and cluster management tasks. They analyze cluster state intelligently and execute remediation actions through declarative CRD-driven configuration.

Do I need Kubernetes experience to use AI agents for cluster ops?▼

Experience with Kubernetes is recommended because agents operate on cluster resources and require understanding of CRD configuration, role-based access control, and cluster architecture. The framework handles agent lifecycle and tool integration.

How does observability work with Kubernetes-native AI agents?▼

Observability integrates directly into the agent framework, providing visibility into agent decisions, cluster health analysis results, and automation actions. Tool integrations and role-scoped access enable secure monitoring of agent behavior across operations.

Can AI agents extend functionality with custom tools in Kubernetes?▼

Yes, the framework supports extensibility through tool integrations that augment agent capabilities. Custom tools integrate with the CRD lifecycle, enabling agents to execute specialized cluster operations and interact with external systems securely.

What security controls limit agent access to cluster resources?▼

Role-scoped access ensures agents operate only within authorized permissions. CRD-driven lifecycle and role-based configuration prevent unauthorized resource modifications while maintaining secure agent operation across the cluster.