--- title: "agentset vs storm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentset-ai-agentset-vs-stanford-oval-storm" tools: ["agentset-ai-agentset", "stanford-oval-storm"] --- # agentset vs storm *GraphCanon updated Aug 17, 2026* ## Verdict Pick agentset if agentSet is a Retrieval-Augmented Generation (RAG) platform emphasizing built-in citations and support for deep research. It's designed to handle diverse file formats while ensuring effective memory management; pick storm if storm is an advanced AI tool that utilizes LLM technology and RAG to generate deep research reports with citations. [agentset](https://agentset.ai) reports 2.0k GitHub stars, 183 forks, and 13 open issues, last pushed Jul 16, 2026. [storm](http://storm.genie.stanford.edu) has 31k stars, 2.9k forks, and 108 open issues, last pushed Sep 30, 2025. Figures are from public GitHub metadata via [agentset's repository](https://github.com/agentset-ai/agentset) and [storm's repository](https://github.com/stanford-oval/storm). | | [agentset](/tools/agentset-ai-agentset.md) | [storm](/tools/stanford-oval-storm.md) | | --- | --- | --- | | Tagline | The open-source RAG platform with built-in citations and support for deep research | An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations. | | Stars | 2,035 | 31,026 | | Forks | 183 | 2,904 | | Open issues | 13 | 108 | | Language | TypeScript | Python | | Adopt for | AgentSet is a Retrieval-Augmented Generation (RAG) platform emphasizing built-in citations and support for deep research. It's designed to handle diverse file formats while ensuring effective memory management. | Storm is an advanced AI tool that utilizes LLM technology and RAG to generate deep research reports with citations. | | Persona | - | - | | Runtime | - | - | | License | AgentSet operates under the MIT License, allowing for broad usage and modification rights. | MIT | | Categories | AI Agents, Data & Retrieval | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentset](/tools/agentset-ai-agentset.md) | [storm](/tools/stanford-oval-storm.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 6d | 320d | | Open issues (now) | 13 | 108 | | Stars delta | Unknown | +895 (30d) | | Open issues delta | Unknown | -36 (30d) | | Full report | [trust report](/tools/agentset-ai-agentset/trust.md) | [trust report](/tools/stanford-oval-storm/trust.md) | ## Decision facts: agentset - **Pricing:** freemium - Free to use as it is open-source. - **Requirements:** Primarily developed in TypeScript.; Best used with an understanding of Retrieval-Augmented Generation and AI agent functionalities. - **Adopt for:** AgentSet is a Retrieval-Augmented Generation (RAG) platform emphasizing built-in citations and support for deep research. It's designed to handle diverse file formats while ensuring effective memory management. - **License detail:** AgentSet operates under the MIT License, allowing for broad usage and modification rights. ## Decision facts: storm - **Adopt for:** Storm is an advanced AI tool that utilizes LLM technology and RAG to generate deep research reports with citations. ## Choose when ### Choose agentset if… - agentset is primarily TypeScript; storm is Python. - Pricing: Free to use as it is open-source.. - Requirements: Primarily developed in TypeScript.; Best used with an understanding of Retrieval-Augmented Generation and AI agent functionalities.. - Tags unique to agentset: ai-agents, embeddings, memory-management, rag. - Also covers AI Agents. - - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats. ### Choose storm if… - storm is primarily Python; agentset is TypeScript. - Tags unique to storm: deep-research, knowledge-curation, large language models, report-generation. - Also covers LLM Frameworks. - When you need comprehensive reports that are heavily researched and reference a wide variety of sources. ## When NOT to use agentset - - Avoid selecting AgentSet if your application does not benefit from or necessitate support for a wide array of file types, as its complexity might overwhelm simpler use-cases. - - If seamless integration with third-party citation services is more preferred, another tool might be better suited since AgentSet focuses on built-in citation capabilities. ## When NOT to use storm - When real-time interaction or rapid iterative feedback loops are necessary, as Storm’s focus on thorough research might lead to longer processing times. - In scenarios requiring manual curation and subjective analysis that goes beyond the capabilities of retrieval and generation mechanisms. ## Common questions ### What is the difference between agentset and storm? agentset: The open-source RAG platform with built-in citations and support for deep research. storm: An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentset over storm? Choose agentset over storm when agentset is primarily TypeScript; storm is Python; Pricing: Free to use as it is open-source.; Requirements: Primarily developed in TypeScript.; Best used with an understanding of Retrieval-Augmented Generation and AI agent functionalities.; Tags unique to agentset: ai-agents, embeddings, memory-management, rag; Also covers AI Agents; - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats. ### When should I choose storm over agentset? Choose storm over agentset when storm is primarily Python; agentset is TypeScript; Tags unique to storm: deep-research, knowledge-curation, large language models, report-generation; Also covers LLM Frameworks; When you need comprehensive reports that are heavily researched and reference a wide variety of sources. ### When should I avoid agentset? - Avoid selecting AgentSet if your application does not benefit from or necessitate support for a wide array of file types, as its complexity might overwhelm simpler use-cases. - If seamless integration with third-party citation services is more preferred, another tool might be better suited since AgentSet focuses on built-in citation capabilities. ### When should I avoid storm? When real-time interaction or rapid iterative feedback loops are necessary, as Storm’s focus on thorough research might lead to longer processing times. In scenarios requiring manual curation and subjective analysis that goes beyond the capabilities of retrieval and generation mechanisms. ### Is agentset or storm more popular on GitHub? storm has more GitHub stars (31,026 vs 2,035). Stars measure visibility, not whether either tool fits your constraints. ### Are agentset and storm open source? Yes - both are open-source projects on GitHub (agentset: MIT, storm: MIT). ### Where can I find alternatives to agentset or storm? GraphCanon lists graph-backed alternatives at [agentset alternatives](/tools/agentset-ai-agentset/alternatives) and [storm alternatives](/tools/stanford-oval-storm/alternatives) ([agentset markdown twin](/tools/agentset-ai-agentset/alternatives.md), [storm markdown twin](/tools/stanford-oval-storm/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/agentset-ai-agentset-vs-stanford-oval-storm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentset or storm? agentset: Very active. storm: Slowing. 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 agentset and storm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentset trust report](/tools/agentset-ai-agentset/trust); [storm trust report](/tools/stanford-oval-storm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentset-ai-agentset`](/api/graphcanon/graph?tool=agentset-ai-agentset) - 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/_