--- title: "agentfield vs agent-kernel" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agent-field-agentfield-vs-yaalalabs-agent-kernel" tools: ["agent-field-agentfield", "yaalalabs-agent-kernel"] --- # agentfield vs agent-kernel *GraphCanon updated Aug 9, 2026* ## Verdict Pick agentfield if agent-Field/agentfield is a comprehensive toolset built in Go under the Apache-2.0 license, aiming to streamline the development lifecycle of scalable AI agents that are observably secure; 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. [agentfield](http://www.agentfield.ai) reports 2.5k GitHub stars, 392 forks, and 74 open issues, last pushed Aug 1, 2026. [agent-kernel](https://kernel.yaala.ai/) has 113 stars, 60 forks, and 128 open issues, last pushed Aug 7, 2026. Figures are from public GitHub metadata via [agentfield's repository](https://github.com/Agent-Field/agentfield) and [agent-kernel's repository](https://github.com/yaalalabs/agent-kernel). | | [agentfield](/tools/agent-field-agentfield.md) | [agent-kernel](/tools/yaalalabs-agent-kernel.md) | | --- | --- | --- | | Tagline | Build, run and scale AI agents like API and microservices | The Operating System for Scalable Enterprise AI Agents | | Stars | 2,472 | 113 | | Forks | 392 | 60 | | Open issues | 74 | 128 | | Language | Go | Python | | Adopt for | Agent-Field/agentfield is a comprehensive toolset built in Go under the Apache-2.0 license, aiming to streamline the development lifecycle of scalable AI agents that are observably secure. | 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 | Apache-2.0 | Apache-2.0 | | Categories | AI Agents | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentfield](/tools/agent-field-agentfield.md) | [agent-kernel](/tools/yaalalabs-agent-kernel.md) | | --- | --- | --- | | Days since push | 0d | 2d | | Open issues (now) | 74 | 128 | | Full report | [trust report](/tools/agent-field-agentfield/trust.md) | [trust report](/tools/yaalalabs-agent-kernel/trust.md) | ## Decision facts: agentfield - **Adopt for:** Agent-Field/agentfield is a comprehensive toolset built in Go under the Apache-2.0 license, aiming to streamline the development lifecycle of scalable AI agents that are observably secure. ## 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 agentfield if… - agentfield is primarily Go; agent-kernel is Python. - Tags unique to agentfield: agent-auth, agent-authentication, agent-scaling, agentic-ai. - When you seek to manage and scale your AI agents with robust identity awareness and auditability features from inception. ### Choose agent-kernel if… - agent-kernel is primarily Python; agentfield is Go. - 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 agentfield - If your project requires heavy customization in languages other than Go as Agentfield is primarily built using Go which may limit its adaptability in polyglot environments. ## 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 agentfield and agent-kernel? agentfield: Build, run and scale AI agents like API and microservices. 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 agentfield over agent-kernel? Choose agentfield over agent-kernel when agentfield is primarily Go; agent-kernel is Python; Tags unique to agentfield: agent-auth, agent-authentication, agent-scaling, agentic-ai; When you seek to manage and scale your AI agents with robust identity awareness and auditability features from inception. ### When should I choose agent-kernel over agentfield? Choose agent-kernel over agentfield when agent-kernel is primarily Python; agentfield is Go; 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 agentfield? If your project requires heavy customization in languages other than Go as Agentfield is primarily built using Go which may limit its adaptability in polyglot environments. ### 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 agentfield or agent-kernel more popular on GitHub? agentfield has more GitHub stars (2,472 vs 113). Stars measure visibility, not whether either tool fits your constraints. ### Are agentfield and agent-kernel open source? Yes - both are open-source projects on GitHub (agentfield: Apache-2.0, agent-kernel: Apache-2.0). ### Where can I find alternatives to agentfield or agent-kernel? GraphCanon lists graph-backed alternatives at [agentfield alternatives](/tools/agent-field-agentfield/alternatives) and [agent-kernel alternatives](/tools/yaalalabs-agent-kernel/alternatives) ([agentfield markdown twin](/tools/agent-field-agentfield/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/agent-field-agentfield-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, agentfield or agent-kernel? agentfield: 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 agentfield and agent-kernel? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentfield trust report](/tools/agent-field-agentfield/trust); [agent-kernel trust report](/tools/yaalalabs-agent-kernel/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agent-field-agentfield`](/api/graphcanon/graph?tool=agent-field-agentfield) - 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/_