--- title: "ECC vs koog" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/affaan-m-ecc-vs-jetbrains-koog" tools: ["affaan-m-ecc", "jetbrains-koog"] --- # ECC vs koog *GraphCanon updated Sep 20, 2026* ## Verdict Pick ECC if eCC is an agent harness performance optimization system for AI agents and large language models, emphasizing skills, instincts, memory, security, and research-first development; pick koog if koog offers JVM-centric AI agent development with support for wide-ranging deployment environments from Kotlin. [ECC](https://ecc.tools) reports 261k GitHub stars, 39k forks, and 227 open issues, last pushed Sep 17, 2026. [koog](https://docs.koog.ai) has 4.6k stars, 474 forks, and 195 open issues, last pushed Sep 14, 2026. Figures are from public GitHub metadata via [ECC's repository](https://github.com/affaan-m/ECC) and [koog's repository](https://github.com/JetBrains/koog). | | [ECC](/tools/affaan-m-ecc.md) | [koog](/tools/jetbrains-koog.md) | | --- | --- | --- | | Tagline | Agent harness performance optimization system for AI agents and LLMs | A JVM-based framework for building enterprise-ready AI agents | | Stars | 261,432 | 4,579 | | Forks | 39,132 | 474 | | Open issues | 227 | 195 | | Language | JavaScript | Kotlin | | Adopt for | ECC is an agent harness performance optimization system for AI agents and large language models, emphasizing skills, instincts, memory, security, and research-first development. | Koog offers JVM-centric AI agent development with support for wide-ranging deployment environments from Kotlin. | | Persona | - | - | | Runtime | - | - | | License | ECC is available under the MIT license, ensuring it remains free for open-source projects. However, for private repositories, ECC Pro offers a paid GitHub App service. | Apache-2.0 License grants permissive use with attribution requirement. | | Categories | AI Agents, Developer Tools, LLM Frameworks | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ECC](/tools/affaan-m-ecc.md) | [koog](/tools/jetbrains-koog.md) | | --- | --- | --- | | Days since push | 0d | 5d | | Open issues (now) | 227 | 195 | | Stars delta | +21k (30d) | +64 (30d) | | Open issues delta | +105 (30d) | +20 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/affaan-m-ecc/trust.md) | [trust report](/tools/jetbrains-koog/trust.md) | ## Decision facts: ECC - **Pricing:** freemium - ECC is free for open-source projects, but private repositories require a paid subscription starting at $19 per seat per month. - **Requirements:** ECC requires a JavaScript environment and can be installed via guided setup or native plugin commands. - **Adopt for:** ECC is an agent harness performance optimization system for AI agents and large language models, emphasizing skills, instincts, memory, security, and research-first development. - **License detail:** ECC is available under the MIT license, ensuring it remains free for open-source projects. However, for private repositories, ECC Pro offers a paid GitHub App service. ## Decision facts: koog - **Adopt for:** Koog offers JVM-centric AI agent development with support for wide-ranging deployment environments from Kotlin. - **License detail:** Apache-2.0 License grants permissive use with attribution requirement. ## Choose when ### Choose ECC if… - ECC is primarily JavaScript; koog is Kotlin. - License: ECC is MIT, koog is Apache-2.0. - Pricing: ECC is free for open-source projects, but private repositories require a paid subscription starting at $19 per seat per month.. - Requirements: ECC requires a JavaScript environment and can be installed via guided setup or native plugin commands.. - Tags unique to ECC: ai-agents, claude, claude-code, developer-tools. - Also covers LLM Frameworks. - Use ECC when you need to optimize the performance of AI agents and large language models, particularly if you are working with platforms like Claude Code, Codex, Opencode, or Cursor. ### Choose koog if… - koog is primarily Kotlin; ECC is JavaScript. - License: koog is Apache-2.0, ECC is MIT. - Tags unique to koog: agentframework, agentic-ai, agents, ai-agents-framework. - Need JVM-based fault-tolerant AI agents across multiple platforms including Android, iOS, and web browsers ## When NOT to use ECC - Avoid ECC if your project does not require the specific features it offers, such as skills, instincts, memory, security, and research-first development, and if you are looking for a more generalized L ## When NOT to use koog - Primarily working outside of JVM environments, such as pure Python or JavaScript projects without JVM support - Looking for an AI agent framework that does not require JDK 17 or Kotlin 2.3.10 or higher ## Common questions ### What is the difference between ECC and koog? ECC: Agent harness performance optimization system for AI agents and LLMs. koog: A JVM-based framework for building enterprise-ready AI agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose ECC over koog? Choose ECC over koog when ECC is primarily JavaScript; koog is Kotlin; License: ECC is MIT, koog is Apache-2.0; Pricing: ECC is free for open-source projects, but private repositories require a paid subscription starting at $19 per seat per month.; Requirements: ECC requires a JavaScript environment and can be installed via guided setup or native plugin commands.; Tags unique to ECC: ai-agents, claude, claude-code, developer-tools; Also covers LLM Frameworks; Use ECC when you need to optimize the performance of AI agents and large language models, particularly if you are working with platforms like Claude Code, Codex, Opencode, or Cursor. ### When should I choose koog over ECC? Choose koog over ECC when koog is primarily Kotlin; ECC is JavaScript; License: koog is Apache-2.0, ECC is MIT; Tags unique to koog: agentframework, agentic-ai, agents, ai-agents-framework; Need JVM-based fault-tolerant AI agents across multiple platforms including Android, iOS, and web browsers. ### When should I avoid ECC? Avoid ECC if your project does not require the specific features it offers, such as skills, instincts, memory, security, and research-first development, and if you are looking for a more generalized L ### When should I avoid koog? Primarily working outside of JVM environments, such as pure Python or JavaScript projects without JVM support Looking for an AI agent framework that does not require JDK 17 or Kotlin 2.3.10 or higher ### Is ECC or koog more popular on GitHub? ECC has more GitHub stars (261,432 vs 4,579). Stars measure visibility, not whether either tool fits your constraints. ### Are ECC and koog open source? Yes - both are open-source projects on GitHub (ECC: MIT, koog: Apache-2.0). ### Where can I find alternatives to ECC or koog? GraphCanon lists graph-backed alternatives at [ECC alternatives](/tools/affaan-m-ecc/alternatives) and [koog alternatives](/tools/jetbrains-koog/alternatives) ([ECC markdown twin](/tools/affaan-m-ecc/alternatives.md), [koog markdown twin](/tools/jetbrains-koog/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/affaan-m-ecc-vs-jetbrains-koog.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ECC or koog? ECC: Very active. koog: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for ECC and koog? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ECC trust report](/tools/affaan-m-ecc/trust); [koog trust report](/tools/jetbrains-koog/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=affaan-m-ecc`](/api/graphcanon/graph?tool=affaan-m-ecc) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_