Key features
Key features of Koog include:
- Multiplatform development: Deploy agents across JVM, JS, WasmJS, Android, and iOS targets using Kotlin Multiplatform.
- Reliability and fault-tolerance: Handle failures with built-in retries and restore the agent state at specific points during execution with the agent persistence feature.
- Intelligent history compression: Optimize token usage while maintaining context in long-running conversations using advanced built-in history compression techniques.
- Enterprise-ready integrations: Utilize integration with popular JVM frameworks such as Spring Boot and Ktor to embed Koog into your applications.
- Observability with OpenTelemetry exporters: Monitor and debug applications with built-in support for popular observability providers (W&B Weave, Langfuse).
- LLM switching and seamless history adaptation: Switch to a different LLM at any point without losing the existing conversation history, or reroute between multiple LLM providers.
- Integration with JVM and Kotlin applications: Build AI agents with an idiomatic, type-safe Kotlin DSL designed specifically for JVM and Kotlin developers.
- Model Context Protocol integration: Use Model Context Protocol (MCP) tools in AI agents.
- Knowledge retrieval and memory: Retain and retrieve knowledge across conversations using vector embeddings, ranked document storage, and shared agent memory.
- Powerful Streaming API: Process responses in real-time with streaming support and parallel tool calls.
- Modular feature system: Customize agent capabilities through a composable architecture.
- Flexible graph workflows: Design complex agent behaviors using intuitive graph-based workflows.
- Custom tool creation: Enhance your agents with tools that access external systems and APIs.
- Comprehensive tracing: Debug and monitor agent execution with detailed, configurable tracing.