
Write HTML. Render video. Built for agents.
kagent gives you a Kubernetes-native way to define agents, attach tools, and run them through a controller and engine. It supports multiple model providers, MCP tools, and OpenTelemetry tracing, so agent behavior can be managed and observed like other cluster workloads.
Builders who want their agents to run as Kubernetes resources with a CLI and UI around them.
You can build and operate agents declaratively in Kubernetes instead of wiring each one up by hand.
Defines agents as Kubernetes custom resources with system prompts, tools, and model settings.
Connects agents to MCP servers and includes tool servers for Kubernetes, Istio, Helm, Argo, Prometheus, Grafana, Cilium, and more.
Works with OpenAI, Azure OpenAI, Anthropic, Google Vertex AI, Ollama, and custom providers through ModelConfig resources.
Watches custom resources and creates the resources needed to run agents in the cluster.
Provides a web UI and command-line tool for managing agents and tools.
Supports OpenTelemetry tracing so you can inspect what agents and tools are doing.
kagent is a Kubernetes native framework for building AI agents. Kubernetes is the most popular orchestration platform for running workloads, and kagent makes it easy to build, deploy and manage AI agents in Kubernetes. The kagent framework is designed to be easy to understand and use, and to provide a flexible and powerful way to build and manage AI agents.
| Getting Started | Technical Details | Get Involved | Reference |
kubectl workflows.
Kagent has 4 core components:
We welcome contributions! Contributors are expected to respect the kagent Code of Conduct
There are many ways to get involved:
kagent is currently in active development. You can check out the full roadmap in the project Kanban board here.
For instructions on how to run everything locally, see the DEVELOPMENT.md file.
Thanks to all contributors who are helping to make kagent better.
This project is licensed under the Apache 2.0 License.
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