--- title: "agents vs agent-kernel" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/wshobson-agents-vs-yaalalabs-agent-kernel" tools: ["wshobson-agents", "yaalalabs-agent-kernel"] --- # agents vs agent-kernel *GraphCanon updated Sep 20, 2026* ## Verdict Pick agents if the agents tool is a marketplace for plugins that enhances multiple AI agents, offering integration and management capabilities across several platforms, including Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot; pick agent-kernel if agent-kernel provides an operating system for scalable enterprise AI agents, supporting deployment and orchestration at scale with native integration support for MCP and A2A. [agents](https://sethhobson.com) reports 40k GitHub stars, 4.2k forks, and 12 open issues, last pushed Sep 19, 2026. [agent-kernel](https://kernel.yaala.ai/) has 188 stars, 86 forks, and 137 open issues, last pushed Sep 11, 2026. Figures are from public GitHub metadata via [agents's repository](https://github.com/wshobson/agents) and [agent-kernel's repository](https://github.com/yaalalabs/agent-kernel). | | [agents](/tools/wshobson-agents.md) | [agent-kernel](/tools/yaalalabs-agent-kernel.md) | | --- | --- | --- | | Tagline | Multi-harness agentic plugin marketplace for various AI agents | The Operating System for Scalable Enterprise AI Agents | | Stars | 39,823 | 188 | | Forks | 4,246 | 86 | | Open issues | 12 | 137 | | Language | Python | Python | | Adopt for | The agents tool is a marketplace for plugins that enhances multiple AI agents, offering integration and management capabilities across several platforms, including Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot | Agent-kernel provides an operating system for scalable enterprise AI agents, supporting deployment and orchestration at scale with native integration support for MCP and A2A. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Developer Tools | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agents](/tools/wshobson-agents.md) | [agent-kernel](/tools/yaalalabs-agent-kernel.md) | | --- | --- | --- | | Open issues (now) | 12 | 137 | | Stars delta | +895 (30d) | +75 (30d) | | Open issues delta | +7 (30d) | +9 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/wshobson-agents/trust.md) | [trust report](/tools/yaalalabs-agent-kernel/trust.md) | ## Decision facts: agents - **Adopt for:** The agents tool is a marketplace for plugins that enhances multiple AI agents, offering integration and management capabilities across several platforms, including Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot ## Decision facts: agent-kernel - **Requirements:** It requires Python versions between 3.12 and 3.13.x.; Supports deployment to various environments such as AWS Lambda, ECS, Azure Functions, or Container Apps via one Terraform module. - **Adopt for:** Agent-kernel provides an operating system for scalable enterprise AI agents, supporting deployment and orchestration at scale with native integration support for MCP and A2A. ## Choose when ### Choose agents if… - License: agents is MIT, agent-kernel is Apache-2.0. - Tags unique to agents: agent-skills, agentic-ai, automation, prompt-engineering. - Also covers Developer Tools. - You are working specifically within the ecosystems of Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, or Gemini CLI, as it provides tailored plugins for these environments ### Choose agent-kernel if… - License: agent-kernel is Apache-2.0, agents is MIT. - Requirements: It requires Python versions between 3.12 and 3.13.x.; Supports deployment to various environments such as AWS Lambda, ECS, Azure Functions, or Container Apps via one Terraform module.. - Tags unique to agent-kernel: a2a, adk, aws, azure. - If you require seamless scalability across different cloud providers like AWS and Azure without lock-in or rewrites. ## When NOT to use agents - You are working solely within a niche environment that isn't one of the supported platforms (like Claude Code, Codex CLI, etc.) because it may not offer compatible plugins or extensive support - Your project requirements do not include interoperability between multiple AI agents and you only need to leverage functionalities from a single AI agent with a robust in-built plugin ecosystem ## When NOT to use agent-kernel - If your project is confined to a single, specific AI framework which doesn't require the flexibility Agent-kernel offers. - When you do not have Python version 3.12 - 3.13.x, as it's the required runtime environment. ## Common questions ### What is the difference between agents and agent-kernel? agents: Multi-harness agentic plugin marketplace for various AI agents. agent-kernel: The Operating System for Scalable Enterprise AI Agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose agents over agent-kernel? Choose agents over agent-kernel when License: agents is MIT, agent-kernel is Apache-2.0; Tags unique to agents: agent-skills, agentic-ai, automation, prompt-engineering; Also covers Developer Tools; You are working specifically within the ecosystems of Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, or Gemini CLI, as it provides tailored plugins for these environments. ### When should I choose agent-kernel over agents? Choose agent-kernel over agents when License: agent-kernel is Apache-2.0, agents is MIT; Requirements: It requires Python versions between 3.12 and 3.13.x.; Supports deployment to various environments such as AWS Lambda, ECS, Azure Functions, or Container Apps via one Terraform module.; Tags unique to agent-kernel: a2a, adk, aws, azure; If you require seamless scalability across different cloud providers like AWS and Azure without lock-in or rewrites. ### When should I avoid agents? You are working solely within a niche environment that isn't one of the supported platforms (like Claude Code, Codex CLI, etc.) because it may not offer compatible plugins or extensive support Your project requirements do not include interoperability between multiple AI agents and you only need to leverage functionalities from a single AI agent with a robust in-built plugin ecosystem ### When should I avoid agent-kernel? If your project is confined to a single, specific AI framework which doesn't require the flexibility Agent-kernel offers. When you do not have Python version 3.12 - 3.13.x, as it's the required runtime environment. ### Is agents or agent-kernel more popular on GitHub? agents has more GitHub stars (39,823 vs 188). Stars measure visibility, not whether either tool fits your constraints. ### Are agents and agent-kernel open source? Yes - both are open-source projects on GitHub (agents: MIT, agent-kernel: Apache-2.0). ### Where can I find alternatives to agents or agent-kernel? GraphCanon lists graph-backed alternatives at [agents alternatives](/tools/wshobson-agents/alternatives) and [agent-kernel alternatives](/tools/yaalalabs-agent-kernel/alternatives) ([agents markdown twin](/tools/wshobson-agents/alternatives.md), [agent-kernel markdown twin](/tools/yaalalabs-agent-kernel/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/wshobson-agents-vs-yaalalabs-agent-kernel.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agents or agent-kernel? agents: Very active. agent-kernel: 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 agents and agent-kernel? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agents trust report](/tools/wshobson-agents/trust); [agent-kernel trust report](/tools/yaalalabs-agent-kernel/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=wshobson-agents`](/api/graphcanon/graph?tool=wshobson-agents) - 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/_