--- title: "agentscope vs agency" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentscope-ai-agentscope-vs-neurocult-agency" tools: ["agentscope-ai-agentscope", "neurocult-agency"] --- # agentscope vs agency *GraphCanon updated Aug 21, 2026* ## Verdict Pick agentscope if agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design; pick agency if agency is a Go-idiomatic library aimed at developers looking to work with Large Language Models and generative AI techniques. [agentscope](https://docs.agentscope.io/) reports 29k GitHub stars, 3.4k forks, and 354 open issues, last pushed Aug 14, 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 [agentscope's repository](https://github.com/agentscope-ai/agentscope) and [agency's repository](https://github.com/neurocult/agency). | | [agentscope](/tools/agentscope-ai-agentscope.md) | [agency](/tools/neurocult-agency.md) | | --- | --- | --- | | Tagline | Build and run agents you can see, understand and trust. | Library for exploring Large Language Models and generative AI in Go | | Stars | 28,973 | 514 | | Forks | 3,367 | 36 | | Open issues | 354 | 4 | | Language | Python | Go | | Adopt for | agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design | 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, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentscope](/tools/agentscope-ai-agentscope.md) | [agency](/tools/neurocult-agency.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 2d | 589d | | Open issues (now) | 354 | 4 | | Stars delta | +1.0k (30d) | +2 (30d) | | Open issues delta | +70 (30d) | 0 (30d) | | Full report | [trust report](/tools/agentscope-ai-agentscope/trust.md) | [trust report](/tools/neurocult-agency/trust.md) | **Typed relationship:** agentscope _(integrates with)_ agency 'Agency' could integrate with 'Agentscope' to build and run agents that are observable, understandable, and trustworthy. ## Decision facts: agentscope - **Adopt for:** agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design ## 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 agentscope if… - agentscope is primarily Python; agency is Go. - License: agentscope is Apache-2.0, agency is MIT. - 'Agency' could integrate with 'Agentscope' to build and run agents that are observable, understandable, and trustworthy. - Tags unique to agentscope: agent, chatbot, large language models, llm. - - You need to develop AI agents where transparency and interpretability are critical. ### Choose agency if… - agency is primarily Go; agentscope is Python. - License: agency is MIT, agentscope 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.. - 'Agency' could integrate with 'Agentscope' to build and run agents that are observable, understandable, and trustworthy. - Tags unique to agency: agents, generative-ai, go, language-models. - If you're proficient in Go and want to implement LLMs within a familiar ecosystem, consider agency. ## When NOT to use agentscope - - If your project does not benefit from the transparency features offered by agentscope, and less emphasis is placed on interpretability and more on specialized machine learning tasks without a need ## 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 agentscope and agency? agentscope: Build and run agents you can see, understand and trust.. 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 agentscope over agency? Choose agentscope over agency when agentscope is primarily Python; agency is Go; License: agentscope is Apache-2.0, agency is MIT; 'Agency' could integrate with 'Agentscope' to build and run agents that are observable, understandable, and trustworthy; Tags unique to agentscope: agent, chatbot, large language models, llm; - You need to develop AI agents where transparency and interpretability are critical. ### When should I choose agency over agentscope? Choose agency over agentscope when agency is primarily Go; agentscope is Python; License: agency is MIT, agentscope 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.; 'Agency' could integrate with 'Agentscope' to build and run agents that are observable, understandable, and trustworthy; Tags unique to agency: agents, generative-ai, go, language-models; If you're proficient in Go and want to implement LLMs within a familiar ecosystem, consider agency. ### When should I avoid agentscope? - If your project does not benefit from the transparency features offered by agentscope, and less emphasis is placed on interpretability and more on specialized machine learning tasks without a need ### 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 agentscope or agency more popular on GitHub? agentscope has more GitHub stars (28,973 vs 514). Stars measure visibility, not whether either tool fits your constraints. ### Are agentscope and agency open source? Yes - both are open-source projects on GitHub (agentscope: Apache-2.0, agency: MIT). ### Where can I find alternatives to agentscope or agency? GraphCanon lists graph-backed alternatives at [agentscope alternatives](/tools/agentscope-ai-agentscope/alternatives) and [agency alternatives](/tools/neurocult-agency/alternatives) ([agentscope markdown twin](/tools/agentscope-ai-agentscope/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/agentscope-ai-agentscope-vs-neurocult-agency.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentscope or agency? agentscope: 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 agentscope and agency? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentscope trust report](/tools/agentscope-ai-agentscope/trust); [agency trust report](/tools/neurocult-agency/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentscope-ai-agentscope`](/api/graphcanon/graph?tool=agentscope-ai-agentscope) - 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/_