--- title: "agentscope vs agno" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentscope-ai-agentscope-vs-agno-agi-agno" tools: ["agentscope-ai-agentscope", "agno-agi-agno"] --- # agentscope vs agno Neutral, constraint-first comparison with live GitHub stats. | | [agentscope](/tools/agentscope-ai-agentscope.md) | [agno](/tools/agno-agi-agno.md) | | --- | --- | --- | | Tagline | Build and run agents you can see, understand and trust. | Build, run, and manage agent platforms. | | Stars | 27,575 | 41,048 | | Forks | 3,141 | 5,609 | | Open issues | 254 | 1,009 | | Language | Python | Python | | Adopt for | AgentScope is a production-ready agent framework designed for creating and managing intelligent agents, offering functionalities like an event system, permission control, multi-tenancy support, workspace/sandbox support, | Agno is an SDK for building and managing AI agent platforms, featuring robust development capabilities, production-level API features, security measures, extensive integrations, and a user-friendly UI. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Agno is licensed under Apache-2.0, allowing for broad usage in both commercial and open-source projects with attribution requirements. | | Categories | AI Agents | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentscope](/tools/agentscope-ai-agentscope.md) | [agno](/tools/agno-agi-agno.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 254 | 1.0k | | Security scan | No criticals | No lockfile | | Full report | [trust report](/tools/agentscope-ai-agentscope/trust.md) | [trust report](/tools/agno-agi-agno/trust.md) | **Typed relationship:** agentscope _(alternative)_ agno Both Agno and agentscope focus on enabling users to build, run, and understand AI agents effectively. They share the goal of providing transparency and trust in agent development. ## Decision facts: agentscope - **Requirements:** Min 4 GB RAM; Requires Docker; Requires Docker for workspace/backend support. - **Adopt for:** AgentScope is a production-ready agent framework designed for creating and managing intelligent agents, offering functionalities like an event system, permission control, multi-tenancy support, workspace/sandbox support, ## Decision facts: agno - **Pricing:** unknown - **Requirements:** Requires Docker; Requires Python environment setup, and Docker for deployment. - **Adopt for:** Agno is an SDK for building and managing AI agent platforms, featuring robust development capabilities, production-level API features, security measures, extensive integrations, and a user-friendly UI. - **License detail:** Agno is licensed under Apache-2.0, allowing for broad usage in both commercial and open-source projects with attribution requirements. ## Choose when ### Choose agentscope if… - Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for workspace/backend support.. - Both Agno and agentscope focus on enabling users to build, run, and understand AI agents effectively. They share the goal of providing transparency and trust in agent development. - Tags unique to agentscope: multi-agent, large-language-models, react-agent, llm-agent. - Use AgentScope when you need advanced features such as fine-grained permission systems to control tools and resources in detail. ### Choose agno if… - Requirements: Requires Docker; Requires Python environment setup, and Docker for deployment.. - Both Agno and agentscope focus on enabling users to build, run, and understand AI agents effectively. They share the goal of providing transparency and trust in agent development. - Tags unique to agno: agents, python, ai-agents. - Also covers Developer Tools. - - **When you need comprehensive control**: Agno allows full ownership over the AI stack with detailed management and control of data, tools, permissions, context, and memory storage. ## When NOT to use agentscope - Avoid using AgentScope if your project does not require fine-grained permission controls over tools and resources. - It might be unnecessary for projects that don't need seamless integration with a human-in-the-loop through its event system. - Not recommended for applications without the need for multi-tenancy or where session isolation is not critical to functionality. - If your application does not require isolated testing environments (like workspaces/sandboxes), AgentScope might introduce unnecessary complexity. ## When NOT to use agno - - **If you're limited to specific cloud environments**: While Agno supports deployment on any platform with container support, it might not be the best if you need tightly integrated features of a non - containerized single-cloud service. - - **When you seek simplicity over control**: Other tools may offer quicker setup and less configuration but at the cost of deeper customization or management capabilities. ## Common questions ### What is the difference between agentscope and agno? agentscope: Build and run agents you can see, understand and trust.. agno: Build, run, and manage agent platforms.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentscope over agno? Choose agentscope over agno when Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for workspace/backend support.; Both Agno and agentscope focus on enabling users to build, run, and understand AI agents effectively. They share the goal of providing transparency and trust in agent development; Tags unique to agentscope: multi-agent, large-language-models, react-agent, llm-agent; Use AgentScope when you need advanced features such as fine-grained permission systems to control tools and resources in detail. ### When should I choose agno over agentscope? Choose agno over agentscope when Requirements: Requires Docker; Requires Python environment setup, and Docker for deployment.; Both Agno and agentscope focus on enabling users to build, run, and understand AI agents effectively. They share the goal of providing transparency and trust in agent development; Tags unique to agno: agents, python, ai-agents; Also covers Developer Tools; - **When you need comprehensive control**: Agno allows full ownership over the AI stack with detailed management and control of data, tools, permissions, context, and memory storage. ### When should I avoid agentscope? Avoid using AgentScope if your project does not require fine-grained permission controls over tools and resources. It might be unnecessary for projects that don't need seamless integration with a human-in-the-loop through its event system. Not recommended for applications without the need for multi-tenancy or where session isolation is not critical to functionality. If your application does not require isolated testing environments (like workspaces/sandboxes), AgentScope might introduce unnecessary complexity. ### When should I avoid agno? - **If you're limited to specific cloud environments**: While Agno supports deployment on any platform with container support, it might not be the best if you need tightly integrated features of a non containerized single-cloud service. - **When you seek simplicity over control**: Other tools may offer quicker setup and less configuration but at the cost of deeper customization or management capabilities. ### Is agentscope or agno more popular on GitHub? agno has more GitHub stars (41,048 vs 27,575). Stars measure visibility, not whether either tool fits your constraints. ### Are agentscope and agno open source? Yes - both are open-source projects on GitHub (agentscope: Apache-2.0, agno: Apache-2.0). ### Where can I find alternatives to agentscope or agno? GraphCanon lists graph-backed alternatives at /tools/agentscope-ai-agentscope/alternatives and /tools/agno-agi-agno/alternatives (/tools/agentscope-ai-agentscope/alternatives.md, /tools/agno-agi-agno/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 /compare/agentscope-ai-agentscope-vs-agno-agi-agno.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentscope or agno? agentscope: Very active. agno: 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 agentscope and agno? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentscope: /tools/agentscope-ai-agentscope/trust; agno: /tools/agno-agi-agno/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/_