--- title: "agent-control vs agency" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentcontrol-agent-control-vs-neurocult-agency" tools: ["agentcontrol-agent-control", "neurocult-agency"] --- # agent-control vs agency *GraphCanon updated Sep 20, 2026* ## Verdict Pick agent-control if agent-control is a highly configurable and extensible centralized agent control system that governs runtime behavior of agents at scale via UI or SDK/API; pick agency if agency is a Go-idiomatic library aimed at developers looking to work with Large Language Models and generative AI techniques. [agent-control](https://agentcontrol.dev) reports 305 GitHub stars, 51 forks, and 36 open issues, last pushed Sep 9, 2026. [agency](https://github.com/neurocult/agency) has 514 stars, 36 forks, and 4 open issues, last pushed Jan 8, 2025. Figures are from public GitHub metadata via [agent-control's repository](https://github.com/agentcontrol/agent-control) and [agency's repository](https://github.com/neurocult/agency). | | [agent-control](/tools/agentcontrol-agent-control.md) | [agency](/tools/neurocult-agency.md) | | --- | --- | --- | | Tagline | Centralized agent control plane for governing runtime agent behavior at scale | Library for exploring Large Language Models and generative AI in Go | | Stars | 305 | 514 | | Forks | 51 | 36 | | Open issues | 36 | 4 | | Language | Python | Go | | Adopt for | agent-control is a highly configurable and extensible centralized agent control system that governs runtime behavior of agents at scale via UI or SDK/API. | Agency is a Go-idiomatic library aimed at developers looking to work with Large Language Models and generative AI techniques. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-control](/tools/agentcontrol-agent-control.md) | [agency](/tools/neurocult-agency.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 619d | | Open issues (now) | 36 | 4 | | Stars delta | +16 (30d) | +2 (30d) | | Full report | [trust report](/tools/agentcontrol-agent-control/trust.md) | [trust report](/tools/neurocult-agency/trust.md) | ## Decision facts: agent-control - **Adopt for:** agent-control is a highly configurable and extensible centralized agent control system that governs runtime behavior of agents at scale via UI or SDK/API. ## Decision facts: agency - **Pricing:** freemium - Agency is available under MIT license and is free for use, modification, and distribution. Additional services or integrations might involve costs not outlined within the repository. - **Adopt for:** Agency is a Go-idiomatic library aimed at developers looking to work with Large Language Models and generative AI techniques. ## Choose when ### Choose agent-control if… - agent-control is primarily Python; agency is Go. - License: agent-control is Apache-2.0, agency is MIT. - Tags unique to agent-control: agentic-workflow, ai-safety, guardrails, llm. - agent-control ships Docker support for self-hosted deployment. - Use agent-control if you need to centrally manage the behavior of multiple AI agents in production environments. ### Choose agency if… - agency is primarily Go; agent-control is Python. - License: agency is MIT, agent-control is Apache-2.0. - Pricing: Agency is available under MIT license and is free for use, modification, and distribution. Additional services or integrations might involve costs not outlined within the repository.. - Tags unique to agency: agents, generative-ai, go, language models. - Also covers LLM Frameworks. - If you're proficient in Go and want to implement LLMs within a familiar ecosystem, consider agency. ## When NOT to use agent-control - Avoid using agent-control when your project does not require centralized control for large-scale AI agent management. - Not recommended if your setup is simplistic or relies solely on languages other than Python or TypeScript, since the tool primarily supports these two. ## When NOT to use agency - Avoid agency if your primary programming expertise lies outside of the Go ecosystem. - Not recommended if you require real-time performance characteristics that surpass what typical LLM exploration libraries can provide. ## Common questions ### What is the difference between agent-control and agency? agent-control: Centralized agent control plane for governing runtime agent behavior at scale. agency: Library for exploring Large Language Models and generative AI in Go. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-control over agency? Choose agent-control over agency when agent-control is primarily Python; agency is Go; License: agent-control is Apache-2.0, agency is MIT; Tags unique to agent-control: agentic-workflow, ai-safety, guardrails, llm; agent-control ships Docker support for self-hosted deployment; Use agent-control if you need to centrally manage the behavior of multiple AI agents in production environments. ### When should I choose agency over agent-control? Choose agency over agent-control when agency is primarily Go; agent-control is Python; License: agency is MIT, agent-control is Apache-2.0; Pricing: Agency is available under MIT license and is free for use, modification, and distribution. Additional services or integrations might involve costs not outlined within the repository.; Tags unique to agency: agents, generative-ai, go, language models; Also covers LLM Frameworks; If you're proficient in Go and want to implement LLMs within a familiar ecosystem, consider agency. ### When should I avoid agent-control? Avoid using agent-control when your project does not require centralized control for large-scale AI agent management. Not recommended if your setup is simplistic or relies solely on languages other than Python or TypeScript, since the tool primarily supports these two. ### When should I avoid agency? Avoid agency if your primary programming expertise lies outside of the Go ecosystem. Not recommended if you require real-time performance characteristics that surpass what typical LLM exploration libraries can provide. ### Is agent-control or agency more popular on GitHub? agency has more GitHub stars (514 vs 305). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-control and agency open source? Yes - both are open-source projects on GitHub (agent-control: Apache-2.0, agency: MIT). ### Where can I find alternatives to agent-control or agency? GraphCanon lists graph-backed alternatives at [agent-control alternatives](/tools/agentcontrol-agent-control/alternatives) and [agency alternatives](/tools/neurocult-agency/alternatives) ([agent-control markdown twin](/tools/agentcontrol-agent-control/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/agentcontrol-agent-control-vs-neurocult-agency.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-control or agency? agent-control: 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 agent-control and agency? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-control trust report](/tools/agentcontrol-agent-control/trust); [agency trust report](/tools/neurocult-agency/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentcontrol-agent-control`](/api/graphcanon/graph?tool=agentcontrol-agent-control) - 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/_