# Koog

## Docs

- [Creating Custom Features](https://mintlify.wiki/JetBrains/koog/advanced/custom-features.md): Build custom AIAgentFeature implementations to extend agent capabilities
- [Error Handling & Recovery](https://mintlify.wiki/JetBrains/koog/advanced/error-handling.md): Handle failures gracefully with retries, fallbacks, and fault tolerance
- [Kotlin Multiplatform Support](https://mintlify.wiki/JetBrains/koog/advanced/multiplatform.md): Build AI agents for JVM, JS, WasmJS, Android, and iOS platforms
- [Observability & Monitoring](https://mintlify.wiki/JetBrains/koog/advanced/observability.md): Monitor AI agents in production with OpenTelemetry, tracing, and metrics
- [Performance Optimization](https://mintlify.wiki/JetBrains/koog/advanced/performance.md): Optimize AI agents for speed, token usage, and resource efficiency
- [AIAgent](https://mintlify.wiki/JetBrains/koog/api/ai-agent.md): Core interface for building and executing AI agents with graph-based workflows
- [AIAgentEnvironment](https://mintlify.wiki/JetBrains/koog/api/ai-agent-environment.md): Interface for AI agents to interact with tools and report errors
- [AIAgentFeature](https://mintlify.wiki/JetBrains/koog/api/ai-agent-feature.md): Interface for creating extensible agent capabilities through the feature system
- [AIAgentPipeline](https://mintlify.wiki/JetBrains/koog/api/ai-agent-pipeline.md): Feature pipeline providing lifecycle event interception and agent behavior extension
- [AIAgentStrategy](https://mintlify.wiki/JetBrains/koog/api/ai-agent-strategy.md): Interface defining the execution strategy for AI agents
- [PromptExecutor](https://mintlify.wiki/JetBrains/koog/api/prompt-executor.md): Executor for interacting with language models and processing prompts
- [Tool](https://mintlify.wiki/JetBrains/koog/api/tool.md): Base class for creating executable tools that AI agents can invoke
- [Tool Descriptors](https://mintlify.wiki/JetBrains/koog/api/tool-descriptors.md): Schema definitions that describe tool interfaces for LLM consumption
- [ToolRegistry](https://mintlify.wiki/JetBrains/koog/api/tool-registry.md): Central repository for managing and accessing tools available to AI agents
- [Agents](https://mintlify.wiki/JetBrains/koog/concepts/agents.md): Understanding AIAgent - the core orchestrator for building AI agents in Koog
- [Environment](https://mintlify.wiki/JetBrains/koog/concepts/environment.md): Understanding AIAgentEnvironment - safe tool execution and context isolation
- [Features](https://mintlify.wiki/JetBrains/koog/concepts/features.md): Extending agent capabilities with the AIAgentFeature system
- [Strategies](https://mintlify.wiki/JetBrains/koog/concepts/strategies.md): Understanding AIAgentStrategy - defining how agents process inputs and make decisions
- [Tool Registry](https://mintlify.wiki/JetBrains/koog/concepts/tool-registry.md): Managing tool collections with ToolRegistry's type-safe builder pattern
- [Tools](https://mintlify.wiki/JetBrains/koog/concepts/tools.md): Creating and using tools to extend AI agent capabilities
- [ACP Agent Integration](https://mintlify.wiki/JetBrains/koog/examples/acp-agent.md): Connect Koog agents to IntelliJ IDEA using the Agent Communication Protocol
- [Building a Code Agent](https://mintlify.wiki/JetBrains/koog/examples/code-agent.md): A progressive, 5-step tutorial for building a production-ready coding agent
- [Examples Overview](https://mintlify.wiki/JetBrains/koog/examples/overview.md): Explore practical examples demonstrating the Koog AI agent framework
- [Simple Agent Examples](https://mintlify.wiki/JetBrains/koog/examples/simple-agent.md): A comprehensive collection of Koog agent examples from basic to advanced
- [Spring Boot Integration](https://mintlify.wiki/JetBrains/koog/examples/spring-boot-integration.md): Production-ready Spring Boot application with Koog agents and REST API
- [Trip Planning Agent](https://mintlify.wiki/JetBrains/koog/examples/trip-planning.md): Advanced agent integrating multiple APIs for intelligent trip planning
- [Event Handlers](https://mintlify.wiki/JetBrains/koog/features/event-handlers.md): Hook into agent lifecycle events for custom logic and monitoring
- [History Compression](https://mintlify.wiki/JetBrains/koog/features/history-compression.md): Intelligent conversation history compression to manage context limits
- [Long-term Memory](https://mintlify.wiki/JetBrains/koog/features/longterm-memory.md): Persistent memory with vector search (RAG) for storing knowledge across sessions
- [Memory](https://mintlify.wiki/JetBrains/koog/features/memory.md): Short-term memory for storing and retrieving facts during agent execution
- [OpenTelemetry](https://mintlify.wiki/JetBrains/koog/features/opentelemetry.md): Industry-standard observability with OpenTelemetry integration
- [Features Overview](https://mintlify.wiki/JetBrains/koog/features/overview.md): Powerful features that extend agent capabilities in the Koog framework
- [Persistence (Checkpoints)](https://mintlify.wiki/JetBrains/koog/features/persistence.md): Save and restore complete agent state with checkpoints
- [Tracing](https://mintlify.wiki/JetBrains/koog/features/tracing.md): Comprehensive execution tracing for debugging and analysis
- [Adding Tools](https://mintlify.wiki/JetBrains/koog/guides/adding-tools.md): Create and register custom tools to extend your agent's capabilities
- [Creating Your First Agent](https://mintlify.wiki/JetBrains/koog/guides/creating-your-first-agent.md): Step-by-step tutorial to build your first AI agent from scratch
- [Graph Workflows](https://mintlify.wiki/JetBrains/koog/guides/graph-workflows.md): Build complex multi-step workflows using graph-based strategies
- [Multi-Agent Systems](https://mintlify.wiki/JetBrains/koog/guides/multi-agent-systems.md): Build systems where agents communicate and collaborate using the A2A protocol
- [Streaming](https://mintlify.wiki/JetBrains/koog/guides/streaming.md): Stream agent responses and handle real-time updates
- [Testing Agents](https://mintlify.wiki/JetBrains/koog/guides/testing-agents.md): Test agents with mocked LLMs and tools using the agents-test framework
- [Installation](https://mintlify.wiki/JetBrains/koog/installation.md): Add Koog to your Kotlin project using Gradle or Maven
- [Agent Client Protocol (ACP)](https://mintlify.wiki/JetBrains/koog/integrations/agent-client-protocol.md): Enable bidirectional communication between Koog agents and client applications
- [Embeddings](https://mintlify.wiki/JetBrains/koog/integrations/embeddings.md): Generate and compare vector embeddings for semantic similarity analysis
- [Ktor Integration](https://mintlify.wiki/JetBrains/koog/integrations/ktor.md): Build AI-powered web services with Koog agents in Ktor applications
- [Model Context Protocol (MCP)](https://mintlify.wiki/JetBrains/koog/integrations/model-context-protocol.md): Connect Koog agents to MCP servers for seamless tool integration
- [RAG (Retrieval-Augmented Generation)](https://mintlify.wiki/JetBrains/koog/integrations/rag.md): Build document retrieval systems with vector storage and semantic search
- [Spring Boot Integration](https://mintlify.wiki/JetBrains/koog/integrations/spring-boot.md): Auto-configuration and dependency injection for Koog agents in Spring Boot applications
- [Introduction to Koog](https://mintlify.wiki/JetBrains/koog/introduction.md): Learn about Koog, the Kotlin multiplatform framework for building predictable, fault-tolerant AI agents
- [Anthropic Provider](https://mintlify.wiki/JetBrains/koog/llm-providers/anthropic.md): Use Anthropic's Claude models with extended thinking and long context capabilities
- [AWS Bedrock Provider](https://mintlify.wiki/JetBrains/koog/llm-providers/bedrock.md): Enterprise AI on AWS with multiple model families and built-in guardrails
- [DashScope Provider](https://mintlify.wiki/JetBrains/koog/llm-providers/dashscope.md): Alibaba Cloud's Qwen models with 1M token context and multimodal capabilities
- [DeepSeek Provider](https://mintlify.wiki/JetBrains/koog/llm-providers/deepseek.md): Cost-effective AI models with strong code generation capabilities
- [Google Provider](https://mintlify.wiki/JetBrains/koog/llm-providers/google.md): Use Google's Gemini models with multimodal capabilities and massive context windows
- [Mistral AI Provider](https://mintlify.wiki/JetBrains/koog/llm-providers/mistralai.md): Advanced AI models with multimodal capabilities, vision, and specialized coding models
- [Ollama Provider](https://mintlify.wiki/JetBrains/koog/llm-providers/ollama.md): Run open-source LLMs locally with Ollama for free, private AI development
- [OpenAI Provider](https://mintlify.wiki/JetBrains/koog/llm-providers/openai.md): Use OpenAI's GPT models including GPT-4o, GPT-5, and o-series reasoning models
- [OpenRouter Provider](https://mintlify.wiki/JetBrains/koog/llm-providers/openrouter.md): Access 100+ LLM providers through one unified API with automatic fallbacks
- [LLM Providers Overview](https://mintlify.wiki/JetBrains/koog/llm-providers/overview.md): Compare and choose the right LLM provider for your Koog AI agents
- [Quickstart](https://mintlify.wiki/JetBrains/koog/quickstart.md): Build your first AI agent with Koog in 5 minutes