--- title: "agentfield vs agency" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agent-field-agentfield-vs-neurocult-agency" tools: ["agent-field-agentfield", "neurocult-agency"] --- # agentfield vs agency *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 agency if agency is a Go-based library for working with Large Language Models (LLMs) and generative AI, aimed at providing developers with a clean and idiomatic approach. [agentfield](http://www.agentfield.ai) reports 2.3k GitHub stars, 371 forks, and 91 open issues, last pushed Jul 10, 2026. [agency](https://github.com/neurocult/agency) has 512 stars, 36 forks, and 4 open issues, last pushed Jan 8, 2025. Figures are from public GitHub metadata via [agentfield's repository](https://github.com/Agent-Field/agentfield) and [agency's repository](https://github.com/neurocult/agency). | | [agentfield](/tools/agent-field-agentfield.md) | [agency](/tools/neurocult-agency.md) | | --- | --- | --- | | Tagline | Build, run and scale AI agents like API and microservices | 🕵️♂️ Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach. | | Stars | 2,339 | 512 | | Forks | 371 | 36 | | Open issues | 91 | 4 | | Language | Go | Go | | 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. | Agency is a Go-based library for working with Large Language Models (LLMs) and generative AI, aimed at providing developers with a clean and idiomatic approach. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents | LLM Frameworks, Vector Databases, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentfield](/tools/agent-field-agentfield.md) | [agency](/tools/neurocult-agency.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 549d | | Open issues (now) | 91 | 4 | | Full report | [trust report](/tools/agent-field-agentfield/trust.md) | [trust report](/tools/neurocult-agency/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: agency - **Adopt for:** Agency is a Go-based library for working with Large Language Models (LLMs) and generative AI, aimed at providing developers with a clean and idiomatic approach. ## Choose when ### Choose agentfield if… - License: agentfield is Apache-2.0, agency 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 agency if… - License: agency is MIT, agentfield is Apache-2.0. - Tags unique to agency: agents, ai, artificial-intelligence, generative-ai. - Also covers LLM Frameworks, Vector Databases. - Use Agency if you are already leveraging the Go language in your development environment. It would be especially fitting if you aim to maintain consistency across all parts of your tech stack without羰 ## 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 agency - Avoid using Agency if you have no experience with Go and prefer a different programming language due to the learning curve. - Do not use Agency if your project's complexity requires frequent updates which are not natively supported, as it might require additional tooling that competitors may offer directly. ## Common questions ### What is the difference between agentfield and agency? agentfield: Build, run and scale AI agents like API and microservices. agency: 🕵️♂️ Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentfield over agency? Choose agentfield over agency when License: agentfield is Apache-2.0, agency 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 agency over agentfield? Choose agency over agentfield when License: agency is MIT, agentfield is Apache-2.0; Tags unique to agency: agents, ai, artificial-intelligence, generative-ai; Also covers LLM Frameworks, Vector Databases; Use Agency if you are already leveraging the Go language in your development environment. It would be especially fitting if you aim to maintain consistency across all parts of your tech stack without羰. ### 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 agency? Avoid using Agency if you have no experience with Go and prefer a different programming language due to the learning curve. Do not use Agency if your project's complexity requires frequent updates which are not natively supported, as it might require additional tooling that competitors may offer directly. ### Is agentfield or agency more popular on GitHub? agentfield has more GitHub stars (2,339 vs 512). Stars measure visibility, not whether either tool fits your constraints. ### Are agentfield and agency open source? Yes - both are open-source projects on GitHub (agentfield: Apache-2.0, agency: MIT). ### Where can I find alternatives to agentfield or agency? GraphCanon lists graph-backed alternatives at [agentfield alternatives](/tools/agent-field-agentfield/alternatives) and [agency alternatives](/tools/neurocult-agency/alternatives) ([agentfield markdown twin](/tools/agent-field-agentfield/alternatives.md), [agency markdown twin](/tools/neurocult-agency/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-neurocult-agency.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentfield or agency? agentfield: Very active. agency: Dormant. 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 agency? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentfield trust report](/tools/agent-field-agentfield/trust); [agency trust report](/tools/neurocult-agency/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/_