--- title: "agentset vs gpt-researcher" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentset-ai-agentset-vs-assafelovic-gpt-researcher" tools: ["agentset-ai-agentset", "assafelovic-gpt-researcher"] --- # agentset vs gpt-researcher *GraphCanon updated Aug 22, 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 gpt-researcher if gpt-researcher is an autonomous agent that uses Language Model Providers to conduct deep research automatically, supporting various installation methods including Docker and deployment as a Claude Skill. [agentset](https://agentset.ai) reports 2.1k GitHub stars, 185 forks, and 14 open issues, last pushed Jul 16, 2026. [gpt-researcher](https://gptr.dev) has 29k stars, 3.9k forks, and 192 open issues, last pushed Jul 18, 2026. Figures are from public GitHub metadata via [agentset's repository](https://github.com/agentset-ai/agentset) and [gpt-researcher's repository](https://github.com/assafelovic/gpt-researcher). | | [agentset](/tools/agentset-ai-agentset.md) | [gpt-researcher](/tools/assafelovic-gpt-researcher.md) | | --- | --- | --- | | Tagline | The open-source RAG platform with built-in citations and support for deep research | An autonomous agent that conducts deep research using LLM providers | | Stars | 2,066 | 28,883 | | Forks | 185 | 3,916 | | Open issues | 14 | 192 | | 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. | gpt-researcher is an autonomous agent that uses Language Model Providers to conduct deep research automatically, supporting various installation methods including Docker and deployment as a Claude Skill. | | Persona | - | - | | Runtime | - | - | | License | AgentSet operates under the MIT License, allowing for broad usage and modification rights. | Apache-2.0 | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentset](/tools/agentset-ai-agentset.md) | [gpt-researcher](/tools/assafelovic-gpt-researcher.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Active (82%) | | Days since push | 36d | 21d | | Open issues (now) | 14 | 192 | | Stars delta | +31 (30d) | +737 (30d) | | Open issues delta | +1 (30d) | -18 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/agentset-ai-agentset/trust.md) | [trust report](/tools/assafelovic-gpt-researcher/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: gpt-researcher - **Pricing:** freemium - The core functionality of gpt-researcher under Apache-2.0 license is free to use, however, users need API keys from external Language Model Providers like OpenAI and Tavily, which are subject to their - **Adopt for:** gpt-researcher is an autonomous agent that uses Language Model Providers to conduct deep research automatically, supporting various installation methods including Docker and deployment as a Claude Skill. ## Choose when ### Choose agentset if… - agentset is primarily TypeScript; gpt-researcher is Python. - License: agentset is MIT, gpt-researcher is Apache-2.0. - 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: agentic-rag, ai-agents, embeddings, memory-management. - - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats. ### Choose gpt-researcher if… - gpt-researcher is primarily Python; agentset is TypeScript. - License: gpt-researcher is Apache-2.0, agentset is MIT. - Pricing: The core functionality of gpt-researcher under Apache-2.0 license is free to use, however, users need API keys from external Language Model Providers like OpenAI and Tavily, which are subject to their. - Tags unique to gpt-researcher: agent, ai, automation, deepresearch. - gpt-researcher ships Docker support for self-hosted deployment. - - When you require automated in-depth research capabilities across diverse LLM providers like OpenAI and Tavily. ## 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 gpt-researcher - - If your setup strictly adheres to a specific tool that does not support the extension of capabilities through skills like Claude Skills. - - In scenarios with stringent network restrictions where running an autonomous agent on top of various LLM providers is prohibited or poses security risks. ## Common questions ### What is the difference between agentset and gpt-researcher? agentset: The open-source RAG platform with built-in citations and support for deep research. gpt-researcher: An autonomous agent that conducts deep research using LLM providers. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentset over gpt-researcher? Choose agentset over gpt-researcher when agentset is primarily TypeScript; gpt-researcher is Python; License: agentset is MIT, gpt-researcher is Apache-2.0; 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: agentic-rag, ai-agents, embeddings, memory-management; - Use AgentSet when you require deep integration with multiple file types including over 22 supported formats. ### When should I choose gpt-researcher over agentset? Choose gpt-researcher over agentset when gpt-researcher is primarily Python; agentset is TypeScript; License: gpt-researcher is Apache-2.0, agentset is MIT; Pricing: The core functionality of gpt-researcher under Apache-2.0 license is free to use, however, users need API keys from external Language Model Providers like OpenAI and Tavily, which are subject to their; Tags unique to gpt-researcher: agent, ai, automation, deepresearch; gpt-researcher ships Docker support for self-hosted deployment; - When you require automated in-depth research capabilities across diverse LLM providers like OpenAI and Tavily. ### 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 gpt-researcher? - If your setup strictly adheres to a specific tool that does not support the extension of capabilities through skills like Claude Skills. - In scenarios with stringent network restrictions where running an autonomous agent on top of various LLM providers is prohibited or poses security risks. ### Is agentset or gpt-researcher more popular on GitHub? gpt-researcher has more GitHub stars (28,883 vs 2,066). Stars measure visibility, not whether either tool fits your constraints. ### Are agentset and gpt-researcher open source? Yes - both are open-source projects on GitHub (agentset: MIT, gpt-researcher: Apache-2.0). ### Where can I find alternatives to agentset or gpt-researcher? GraphCanon lists graph-backed alternatives at [agentset alternatives](/tools/agentset-ai-agentset/alternatives) and [gpt-researcher alternatives](/tools/assafelovic-gpt-researcher/alternatives) ([agentset markdown twin](/tools/agentset-ai-agentset/alternatives.md), [gpt-researcher markdown twin](/tools/assafelovic-gpt-researcher/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-assafelovic-gpt-researcher.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentset or gpt-researcher? agentset: Steady. gpt-researcher: 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 agentset and gpt-researcher? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentset trust report](/tools/agentset-ai-agentset/trust); [gpt-researcher trust report](/tools/assafelovic-gpt-researcher/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/_