--- title: "agentfield vs agents" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agent-field-agentfield-vs-wshobson-agents" tools: ["agent-field-agentfield", "wshobson-agents"] --- # agentfield vs agents *GraphCanon updated Jul 12, 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 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. [agentfield](http://www.agentfield.ai) reports 2.3k GitHub stars, 371 forks, and 91 open issues, last pushed Jul 10, 2026. [agents](https://sethhobson.com) has 38k stars, 4.0k forks, and 1 open issues, last pushed Jul 8, 2026. Figures are from public GitHub metadata via [agentfield's repository](https://github.com/Agent-Field/agentfield) and [agents's repository](https://github.com/wshobson/agents). | | [agentfield](/tools/agent-field-agentfield.md) | [agents](/tools/wshobson-agents.md) | | --- | --- | --- | | Tagline | Build, run and scale AI agents like API and microservices | Multi-harness agentic plugin marketplace for various AI agents | | Stars | 2,339 | 37,779 | | Forks | 371 | 4,050 | | Open issues | 91 | 1 | | 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. | 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 | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentfield](/tools/agent-field-agentfield.md) | [agents](/tools/wshobson-agents.md) | | --- | --- | --- | | Days since push | 1d | 2d | | Open issues (now) | 91 | 1 | | Owner type | Organization | User | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/agent-field-agentfield/trust.md) | [trust report](/tools/wshobson-agents/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: 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 ## Choose when ### Choose agentfield if… - agentfield is primarily Go; agents is Python. - License: agentfield is Apache-2.0, agents is MIT. - Tags unique to agentfield: agent-scaling, multiagent, agent-auth, genai. - When you seek to manage and scale your AI agents with robust identity awareness and auditability features from inception. ### Choose agents if… - agents is primarily Python; agentfield is Go. - License: agents is MIT, agentfield is Apache-2.0. - Tags unique to agents: agent-skills, workflows, prompt-engineering, automation. - 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 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 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 ## Common questions ### What is the difference between agentfield and agents? agentfield: Build, run and scale AI agents like API and microservices. agents: Multi-harness agentic plugin marketplace for various AI agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentfield over agents? Choose agentfield over agents when agentfield is primarily Go; agents is Python; License: agentfield is Apache-2.0, agents is MIT; Tags unique to agentfield: agent-scaling, multiagent, agent-auth, genai; When you seek to manage and scale your AI agents with robust identity awareness and auditability features from inception. ### When should I choose agents over agentfield? Choose agents over agentfield when agents is primarily Python; agentfield is Go; License: agents is MIT, agentfield is Apache-2.0; Tags unique to agents: agent-skills, workflows, prompt-engineering, automation; 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 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 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 ### Is agentfield or agents more popular on GitHub? agents has more GitHub stars (37,779 vs 2,339). Stars measure visibility, not whether either tool fits your constraints. ### Are agentfield and agents open source? Yes - both are open-source projects on GitHub (agentfield: Apache-2.0, agents: MIT). ### Where can I find alternatives to agentfield or agents? GraphCanon lists graph-backed alternatives at [agentfield alternatives](/tools/agent-field-agentfield/alternatives) and [agents alternatives](/tools/wshobson-agents/alternatives) ([agentfield markdown twin](/tools/agent-field-agentfield/alternatives.md), [agents markdown twin](/tools/wshobson-agents/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-wshobson-agents.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentfield or agents? agentfield: Very active. agents: 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 agents? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentfield trust report](/tools/agent-field-agentfield/trust); [agents trust report](/tools/wshobson-agents/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/_