Comparison
agentscope vs agno
agentscope (Build and run agents you can see, understand and trust.) vs agno (Build, run, and manage agent platforms.) - live GitHub stats and typed graph relationships, not marketing.
Markdown twin · agentscope alternatives · agno alternatives
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Tagline
- agentscope
- Build and run agents you can see, understand and trust.
- agno
- Build, run, and manage agent platforms.
Stars
- agentscope
- 28k
- agno
- 41k
Forks
- agentscope
- 3.1k
- agno
- 5.6k
Open issues
- agentscope
- 254
- agno
- 1.0k
Language
- agentscope
- Python
- agno
- Python
Adopt for
- agentscope
- 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
- 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
- agentscope
- -
- agno
- -
Runtime
- agentscope
- -
- agno
- -
License
- agentscope
- Apache-2.0
- agno
- Agno is licensed under Apache-2.0, allowing for broad usage in both commercial and open-source projects with attribution requirements.
Last pushed
- agentscope
- Jul 7, 2026
- agno
- Jul 8, 2026
Categories
- agentscope
- AI Agents
- agno
- AI Agents, Developer Tools
Trust and health
Days since push
- agentscope
- 1d
- agno
- 0d
Open issues (now)
- agentscope
- 254
- agno
- 1.0k
Security scan
- agentscope
- No criticals
- agno
- No lockfile
Full report
- agentscope
- Trust report
- agno
- Trust report
Typed relationship
agentscope alternative agnoBoth 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.
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.
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.
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 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.
Explore
agentscope trust report →agno trust report →AI Agents category →Developer Tools category →All comparisonsStack workflowsTrending tools
Related comparisons
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.