Kagent

What is Kagent?

io and accepted as a CNCF Sandbox project. It is built for platform and DevOps engineers who want AI agents to run where their workloads already live rather than in a separate system.

With Kagent, teams define agents declaratively as Kubernetes custom resources, enabling GitOps workflows, version control and familiar cluster governance.

The runtime is multi-LLM, working with providers such as OpenAI, Anthropic, Gemini and xAI without vendor lock-in, and it has native Model Context Protocol support so agents can connect to APIs and tools.

It includes full observability through OpenTelemetry tracing, Prometheus metrics and structured logging, and security features that are zero-trust ready with Istio and Ambient Mesh support, mTLS and RBAC.

Agents can also discover and invoke one another for multi-agent workflows, and Kagent is compatible with frameworks like LangGraph, CrewAI and Google ADK. Use cases include automating Kubernetes operations, troubleshooting cluster issues, and building custom platform-engineering agents. 0 license with no proprietary tiers, and strong observability and security.

Cons are that it requires Kubernetes expertise to adopt, and as a young sandbox project it is still maturing. Kagent is free and open source, installable via a single Helm chart. Pricing changes often, so check the official site for current plans.

Kagent's core capabilities include Agents defined as Kubernetes custom resources, Multi-LLM support across major providers, Native Model Context Protocol integration, OpenTelemetry tracing and Prometheus metrics, Zero-trust security with mTLS and RBAC and Agent-to-agent multi-agent workflows.

Agents defined as Kubernetes custom resources is built in, Multi-LLM support across major providers is built in, Native Model Context Protocol integration is built in, OpenTelemetry tracing and Prometheus metrics is built in, so you get a rounded toolkit rather than a single trick.

Each feature is designed to take the manual effort out of the task and help you reach a usable result faster, which is what makes Kagent worth a place on your shortlist.

0 license with no paid tiers and Strong observability and security as the reasons they keep using Kagent.

It isn't perfect, though — Requires Kubernetes expertise to adopt and Young sandbox project still maturing are the trade-offs people most often mention, so weigh those against your own priorities before you commit.

As with any AI tool, the output still benefits from a quick human review, but Kagent gets you most of the way there with far less effort.

Kagent runs on a free pricing model, so you can start for free and only pay once you outgrow the free tier — handy for testing it on a real task before spending anything.

AI-tool pricing changes often, so always check the current plans, seats and add-ons on the official site for the latest details before you buy. Who is Kagent for? It's best suited for kubernetes-native runtime for agentic ai.

Whether you're a beginner trying this kind of AI tool for the first time or a professional who'll use it every day, it's a credible option to consider.

If you're still deciding, compare Kagent against the alternatives and the head-to-head comparisons linked below — looking at features, pricing and real user ratings side by side is the fastest way to find the right fit for your workflow and budget.

Who is Kagent for?

Kagent is best suited for kubernetes-native runtime for agentic ai. Whether you are trying this kind of coding & development tool for the first time or use one every day, it is a credible option to shortlist — compare it with the alternatives and head-to-head comparisons linked on this page to find the best fit for your workflow and budget.