Comparison
deep-research vs llm-wiki-agent
Verdict
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; pick llm-wiki-agent if llm-wiki-agent serves as a self-maintained personal knowledge base using AI agents like Claude, Codex, OpenCode, and Gemini CLI.
Markdown twin · deep-research alternatives · llm-wiki-agent alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | deep-research | llm-wiki-agent |
|---|---|---|
| Maintenance | Slowing (129d since push) As of 2d · github_public_v1 | Very active (5d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2d · github_public_v1 | Not a fork · Organization account As of 1w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No published findings from this source as of 2026-07-11 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
- deep-research
- An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.
- llm-wiki-agent
- A personal knowledge base that builds and maintains itself using various AI agents.
Stars
- deep-research
- 20k
- llm-wiki-agent
- 3.3k
Forks
- deep-research
- 2.0k
- llm-wiki-agent
- 388
Open issues
- deep-research
- 93
- llm-wiki-agent
- 3
Language
- deep-research
- TypeScript
- llm-wiki-agent
- Python
Adopt for
- 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.
- llm-wiki-agent
- llm-wiki-agent serves as a self-maintained personal knowledge base using AI agents like Claude, Codex, OpenCode, and Gemini CLI.
Persona
- deep-research
- -
- llm-wiki-agent
- -
Runtime
- deep-research
- -
- llm-wiki-agent
- -
License
- deep-research
- MIT
- llm-wiki-agent
- MIT
Last pushed
- deep-research
- Apr 11, 2026
- llm-wiki-agent
- Aug 3, 2026
Categories
- deep-research
- AI Agents, Data & Retrieval
- llm-wiki-agent
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- deep-research
- Slowing (36%)
- llm-wiki-agent
- Very active (96%)
Days since push
- deep-research
- 129d
- llm-wiki-agent
- 5d
Open issues (now)
- deep-research
- 93
- llm-wiki-agent
- 3
Stars delta
- deep-research
- +195 (30d)
- llm-wiki-agent
- Unknown
Open issues delta
- deep-research
- +3 (30d)
- llm-wiki-agent
- Unknown
Owner type
- deep-research
- User
- llm-wiki-agent
- Organization
OSV dependency advisories
- deep-research
- Published findings
- llm-wiki-agent
- No published findings from this source as of 2026-07-11
Full report
- deep-research
- Trust report
- llm-wiki-agent
- Trust report
Choose deep-research if…
- deep-research is primarily TypeScript; llm-wiki-agent is Python.
- 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.
Choose llm-wiki-agent if…
- llm-wiki-agent is primarily Python; deep-research is TypeScript.
- Tags unique to llm-wiki-agent: ai-agent, automation, knowledge-base, llm.
- When you need to create an interlinked wiki without setting up API keys or configuring Python environments.
When NOT to use llm-wiki-agent
- If the process requires strict privacy controls and no third-party AI agents can be used.
- When your project needs real-time interaction with APIs for dynamic content integration, as llm-wiki-agent does not support API-driven operations.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (SamurAIGPT/llm-wiki-agent) · observed Aug 8, 2026
- GitHub forks (SamurAIGPT/llm-wiki-agent) · observed Aug 8, 2026
- Last push (SamurAIGPT/llm-wiki-agent) · observed Aug 3, 2026
- License file (MIT) · observed Aug 8, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deep-research 20k · llm-wiki-agent 3.3k (synced Aug 19, 2026).
Common questions
- What is the difference between deep-research and llm-wiki-agent?
- deep-research: An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.. llm-wiki-agent: A personal knowledge base that builds and maintains itself using various AI agents.. See the comparison table for live GitHub stats and shared categories.
- When should I choose deep-research over llm-wiki-agent?
- Choose deep-research over llm-wiki-agent when deep-research is primarily TypeScript; llm-wiki-agent is Python; 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 choose llm-wiki-agent over deep-research?
- Choose llm-wiki-agent over deep-research when llm-wiki-agent is primarily Python; deep-research is TypeScript; Tags unique to llm-wiki-agent: ai-agent, automation, knowledge-base, llm; When you need to create an interlinked wiki without setting up API keys or configuring Python environments.
- 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.
- When should I avoid llm-wiki-agent?
- If the process requires strict privacy controls and no third-party AI agents can be used. When your project needs real-time interaction with APIs for dynamic content integration, as llm-wiki-agent does not support API-driven operations.
- Is deep-research or llm-wiki-agent more popular on GitHub?
- deep-research has more GitHub stars (19,571 vs 3,334). Stars measure visibility, not whether either tool fits your constraints.
- Are deep-research and llm-wiki-agent open source?
- Yes - both are open-source projects on GitHub (deep-research: MIT, llm-wiki-agent: MIT).
- Where can I find alternatives to deep-research or llm-wiki-agent?
- GraphCanon lists graph-backed alternatives at deep-research alternatives and llm-wiki-agent alternatives (deep-research markdown twin, llm-wiki-agent 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, deep-research or llm-wiki-agent?
- deep-research: Slowing. llm-wiki-agent: 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 deep-research and llm-wiki-agent?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deep-research trust report; llm-wiki-agent trust report.