JetBrains/koog
Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-browser environments. Koog is based on our AI products expertise and provides proven solutions for complex LLM and AI problems observed · 2026-08-28
Health v2 · maintenance only
84/100
- Activity 99
- Release rhythm 93
- Longevity 34
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 14.5
- age_days: 489
- days_rel: 44
- days_push: 7
- n_releases_24m: 23
Adoption not part of the score
4536 stars · 463 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Koog is a JetBrains-built Kotlin/Java framework for creating fault-tolerant, enterprise-ready AI agents on the JVM, with multiplatform deployment to Android, iOS, JS, and WasmJS via Kotlin Multiplatform. It provides a type-safe Kotlin DSL and fluent Java API for agent workflows, tool use, MCP integration, RAG memory, LLM provider switching, and observability.
Use cases
- build ai agents in kotlin or java
- create llm agents for spring boot backends
- run ai agents on android and ios from one codebase
- add tool calling and mcp support to an llm app
- build multi-agent workflows with graph strategies
- add chat memory and rag to a conversational agent
- switch between openai, anthropic, and ollama models without losing history
- monitor and trace agent execution with opentelemetry
When to choose
- your team works on the JVM with Kotlin or Java and wants idiomatic, type-safe agent APIs
- you need enterprise features like retries, state persistence, and observability out of the box
- you want one agent codebase deployable to JVM, Android, iOS, and browser via Kotlin Multiplatform
- you need Spring Boot or Ktor integration and multi-provider LLM switching
When to avoid
- you want a Python-based agent framework like LangChain or a JS/TS stack
- your project is not on the JVM or Kotlin Multiplatform targets
- you need a minimal, lightweight agent loop without framework abstractions
- you depend on beta modules (planner agents, knowledge retrieval) that may change between releases
Facets
framework · maturity active
agent-framework llm-inference rag mcp chatbot tracing workflow-automation sdk large-language-models artificial-intelligence developer-tools backend mobile-development jvm wasm cross-platform self-hosted kotlin-multiplatform llm-agents spring-boot ktor multi-llm-providers agent-persistence history-compression streaming-api opentelemetry graph-workflows ai-agents android ios docker
10 sources
- readme: https://github.com/JetBrains/koog · fetched 2026-08-28 · 5d9ee394ef1b
- homepage: https://docs.koog.ai · fetched 2026-08-29 · e8e5d8b377c4
- site_page: https://docs.koog.ai/key-features · fetched 2026-08-29 · 1ba020741d10
- site_page: https://docs.koog.ai/quickstart · fetched 2026-08-29 · 88aff341c4c2
- site_page: https://docs.koog.ai/features · fetched 2026-08-29 · c234c566eb4a
- site_page: https://docs.koog.ai/features/agent-event-handlers · fetched 2026-08-29 · 4e8628b455e5
- site_page: https://docs.koog.ai/features/tracing · fetched 2026-08-29 · b7175406a0ab
- site_page: https://docs.koog.ai/features/chat-memory · fetched 2026-08-29 · aabd762fffa9
- site_page: https://docs.koog.ai/features/chat-memory/chat-agent-with-memory · fetched 2026-08-29 · 56442a8429ac
- site_page: https://docs.koog.ai/features/chat-memory/chat-backend-with-memory · fetched 2026-08-29 · 81aa34ee0bf2
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| JetBrains/koog | main | 84 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem