--- title: "agentscope vs pyspur" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentscope-ai-agentscope-vs-pyspur-dev-pyspur" tools: ["agentscope-ai-agentscope", "pyspur-dev-pyspur"] --- # agentscope vs pyspur Neutral, constraint-first comparison with live GitHub stats. | | [agentscope](/tools/agentscope-ai-agentscope.md) | [pyspur](/tools/pyspur-dev-pyspur.md) | | --- | --- | --- | | Tagline | Build and run agents you can see, understand and trust. | A visual playground for agentic workflows | | Stars | 27,575 | 5,749 | | Forks | 3,141 | 428 | | Open issues | 254 | 39 | | Language | Python | TypeScript | | 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, | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | AI Agents | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentscope](/tools/agentscope-ai-agentscope.md) | [pyspur](/tools/pyspur-dev-pyspur.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 1d | 8d | | Open issues (now) | 254 | 39 | | Security scan | No criticals | No lockfile | | Full report | [trust report](/tools/agentscope-ai-agentscope/trust.md) | [trust report](/tools/pyspur-dev-pyspur/trust.md) | **Typed relationship:** agentscope _(alternative)_ pyspur PySpur and agentscope both focus on building and operating AI agents with a strong emphasis on visibility, understanding, and trust. ## Shared compatibility - **Python**: [agentscope](/tools/agentscope-ai-agentscope.md) - Python runtime; [pyspur](/tools/pyspur-dev-pyspur.md) - Python runtime ## 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: pyspur - **Pricing:** unknown - **Requirements:** - Requires Python 3.11 or higher.; - Supports human-in-the-loop workflow management. ## Choose when ### Choose agentscope if… - agentscope is primarily Python; pyspur is TypeScript. - Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for workspace/backend support.. - PySpur and agentscope both focus on building and operating AI agents with a strong emphasis on visibility, understanding, and trust. - 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 pyspur if… - pyspur is primarily TypeScript; agentscope is Python. - Requirements: - Requires Python 3.11 or higher.; - Supports human-in-the-loop workflow management.. - PySpur and agentscope both focus on building and operating AI agents with a strong emphasis on visibility, understanding, and trust. - Tags unique to pyspur: agents, tool, workflow, framework. - pyspur ships Docker support for self-hosted deployment. - - When you need a visual representation for your AI agent's workflow, enabling faster iteration and addressing prompt tweaking frustrations. ## 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 pyspur - - If you prefer a text-based configuration over a visual interface, as PySpur heavily relies on its visual playground to enable rapid iteration. - - When working in an environment where Python 3.11+ is not available or supported, as PySpur requires this version for optimal functionality. ## Common questions ### What is the difference between agentscope and pyspur? agentscope: Build and run agents you can see, understand and trust.. pyspur: A visual playground for agentic workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentscope over pyspur? Choose agentscope over pyspur when agentscope is primarily Python; pyspur is TypeScript; Requirements: Min 4 GB RAM; Requires Docker; Requires Docker for workspace/backend support.; PySpur and agentscope both focus on building and operating AI agents with a strong emphasis on visibility, understanding, and trust; 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 pyspur over agentscope? Choose pyspur over agentscope when pyspur is primarily TypeScript; agentscope is Python; Requirements: - Requires Python 3.11 or higher.; - Supports human-in-the-loop workflow management.; PySpur and agentscope both focus on building and operating AI agents with a strong emphasis on visibility, understanding, and trust; Tags unique to pyspur: agents, tool, workflow, framework; pyspur ships Docker support for self-hosted deployment; - When you need a visual representation for your AI agent's workflow, enabling faster iteration and addressing prompt tweaking frustrations. ### 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 pyspur? - If you prefer a text-based configuration over a visual interface, as PySpur heavily relies on its visual playground to enable rapid iteration. - When working in an environment where Python 3.11+ is not available or supported, as PySpur requires this version for optimal functionality. ### Is agentscope or pyspur more popular on GitHub? agentscope has more GitHub stars (27,575 vs 5,749). Stars measure visibility, not whether either tool fits your constraints. ### Are agentscope and pyspur open source? Yes - both are open-source projects on GitHub (agentscope: Apache-2.0, pyspur: Apache-2.0). ### Where can I find alternatives to agentscope or pyspur? GraphCanon lists graph-backed alternatives at /tools/agentscope-ai-agentscope/alternatives and /tools/pyspur-dev-pyspur/alternatives (/tools/agentscope-ai-agentscope/alternatives.md, /tools/pyspur-dev-pyspur/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-pyspur-dev-pyspur.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentscope or pyspur? agentscope: Very active. pyspur: 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 pyspur? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentscope: /tools/agentscope-ai-agentscope/trust; pyspur: /tools/pyspur-dev-pyspur/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/_