Comparison
agentset vs deep-research
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 deep-research if deep-research is an AI-powered research assistant that leverages search engines, web scraping, and large language models to conduct iterative and in-depth exploration of topics.
Markdown twin · agentset alternatives · deep-research alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | agentset | deep-research |
|---|---|---|
| Maintenance | Very active (6d since push) As of 4w · github_public_v1 | Slowing (129d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4w · github_public_v1 | Not a fork · Personal account As of 1d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- agentset
- The open-source RAG platform with built-in citations and support for deep research
- deep-research
- An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.
Stars
- agentset
- 2.0k
- deep-research
- 20k
Forks
- agentset
- 183
- deep-research
- 2.0k
Open issues
- agentset
- 13
- deep-research
- 93
Language
- agentset
- TypeScript
- deep-research
- TypeScript
Adopt for
- agentset
- 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.
- deep-research
- Deep-research is an AI-powered research assistant that leverages search engines, web scraping, and large language models to conduct iterative and in-depth exploration of topics.
Persona
- agentset
- -
- deep-research
- -
Runtime
- agentset
- -
- deep-research
- -
License
- agentset
- AgentSet operates under the MIT License, allowing for broad usage and modification rights.
- deep-research
- MIT
Last pushed
- agentset
- Jul 16, 2026
- deep-research
- Apr 11, 2026
Categories
- agentset
- AI Agents, Data & Retrieval
- deep-research
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- agentset
- Very active (96%)
- deep-research
- Slowing (36%)
Days since push
- agentset
- 6d
- deep-research
- 129d
Open issues (now)
- agentset
- 13
- deep-research
- 93
Stars delta
- agentset
- Unknown
- deep-research
- +195 (30d)
Open issues delta
- agentset
- Unknown
- deep-research
- +3 (30d)
Owner type
- agentset
- Organization
- deep-research
- User
OSV dependency advisories
- agentset
- No lockfile (source not queried)
- deep-research
- Published findings
Full report
- agentset
- Trust report
- deep-research
- Trust report
Choose agentset if…
- 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 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.
Choose deep-research if…
- Requirements: Requires Docker.
- Tags unique to deep-research: agent, ai, gpt, o3-mini.
- deep-research ships Docker support for self-hosted deployment.
- When you need a tool that can refine its topic focus over time through repeated iterations.
When NOT to use deep-research
- When you prefer a language other than TypeScript, as deep-research specifically requires a Node.js environment.
- If your use case does not necessitate the use of both Firecrawl and OpenAI APIs, preferring instead solutions with more API flexibility or that do not require API keys.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (agentset-ai/agentset) · observed Jul 22, 2026
- GitHub forks (agentset-ai/agentset) · observed Jul 22, 2026
- Last push (agentset-ai/agentset) · observed Jul 16, 2026
- License file (MIT) · observed Jul 22, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (dzhng/deep-research) · observed Aug 19, 2026
- GitHub forks (dzhng/deep-research) · observed Aug 19, 2026
- Last push (dzhng/deep-research) · observed Apr 11, 2026
- License file (MIT) · observed Aug 19, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentset 2.0k · deep-research 20k (synced Jul 22, 2026).
Common questions
- What is the difference between agentset and deep-research?
- agentset: The open-source RAG platform with built-in citations and support for deep research. deep-research: An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentset over deep-research?
- Choose agentset over deep-research when 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 deep-research over agentset?
- Choose deep-research over agentset when Requirements: Requires Docker; Tags unique to deep-research: agent, ai, gpt, o3-mini; deep-research ships Docker support for self-hosted deployment; When you need a tool that can refine its topic focus over time through repeated iterations.
- 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 deep-research?
- When you prefer a language other than TypeScript, as deep-research specifically requires a Node.js environment. If your use case does not necessitate the use of both Firecrawl and OpenAI APIs, preferring instead solutions with more API flexibility or that do not require API keys.
- Is agentset or deep-research more popular on GitHub?
- deep-research has more GitHub stars (19,571 vs 2,035). Stars measure visibility, not whether either tool fits your constraints.
- Are agentset and deep-research open source?
- Yes - both are open-source projects on GitHub (agentset: MIT, deep-research: MIT).
- Where can I find alternatives to agentset or deep-research?
- GraphCanon lists graph-backed alternatives at agentset alternatives and deep-research alternatives (agentset markdown twin, deep-research markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, agentset or deep-research?
- agentset: Very active. deep-research: 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 deep-research?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentset trust report; deep-research trust report.