Comparison
atomic-agents vs langgraph
Verdict
Pick atomic-agents if atomic agents streamline the creation of AI agents with modular integrations, making it ideal for Python-centric projects requiring flexibility and ease-of-use in agent development; pick langgraph if langGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents, offering durable execution, human-in-the-loop oversight, and comprehensive memory management.
Markdown twin · atomic-agents alternatives · langgraph alternatives
GraphCanon updated Sep 20, 2026
10views this month
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Trust & integrity
| Signal | atomic-agents | langgraph |
|---|---|---|
| Maintenance | Very active (1d since push) As of Aug 17, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Aug 17, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · 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
- atomic-agents
- Building AI agents, atomically
- langgraph
- Low-level orchestration framework for building stateful agents
Stars
- atomic-agents
- 6.2k
- langgraph
- 42k
Forks
- atomic-agents
- 533
- langgraph
- 7.1k
Open issues
- atomic-agents
- 4
- langgraph
- 794
Language
- atomic-agents
- Python
- langgraph
- Python
Adopt for
- atomic-agents
- Atomic agents streamline the creation of AI agents with modular integrations, making it ideal for Python-centric projects requiring flexibility and ease-of-use in agent development.
- langgraph
- LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents, offering durable execution, human-in-the-loop oversight, and comprehensive memory management.
Persona
- atomic-agents
- -
- langgraph
- -
Runtime
- atomic-agents
- -
- langgraph
- -
License
- atomic-agents
- MIT
- langgraph
- MIT
Last pushed
- atomic-agents
- Aug 16, 2026
- langgraph
- Sep 18, 2026
Categories
- atomic-agents
- AI Agents, LLM Frameworks
- langgraph
- AI Agents
Trust and health
Days since push
- atomic-agents
- 1d
- langgraph
- 0d
Open issues (now)
- atomic-agents
- 4
- langgraph
- 794
Stars delta
- atomic-agents
- +134 (30d)
- langgraph
- +3.5k (30d)
Open issues delta
- atomic-agents
- -2 (30d)
- langgraph
- +147 (30d)
Owner type
- atomic-agents
- User
- langgraph
- Organization
OSV dependency advisories
- atomic-agents
- Published findings
- langgraph
- No lockfile (source not queried)
Full report
- atomic-agents
- Trust report
- langgraph
- Trust report
Shared compatibility
- Python · atomic-agents: Python runtime · langgraph: Python runtime
Choose atomic-agents if…
- Tags unique to atomic-agents: ai, artificial-intelligence, large-language-model, llms.
- Also covers LLM Frameworks.
- When you need a flexible toolkit to create atomic, modular AI agents with various LLM provider support
When NOT to use atomic-agents
- Avoid for projects needing exclusive use of providers not listed in the Instructor docs
- Not suitable if looking for a solution that is language-agnostic, as it’s tightly integrated with Python ecosystems and CLI utilities
Choose langgraph if…
- Tags unique to langgraph: agents, ai-agents, framework, langchain.
- When you need to build agents that can persist through failures and resume from where they left off, ensuring durable execution.
- More GitHub stars (42k vs 6.2k) - visibility, not fit.
When NOT to use langgraph
- If you are looking for a higher-level package that simplifies the process of building agents with planning and subagent capabilities, consider Deep Agents instead.
- For projects that do not require long-running, stateful workflows, LangGraph's features may be overkill and a simpler framework might be more appropriate.
- If your project is primarily focused on JavaScript or TypeScript, LangGraph.js might be a better fit, as LangGraph is primarily designed for Python environments.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Eigenwise/atomic-agents) · observed Sep 20, 2026
- GitHub forks (Eigenwise/atomic-agents) · observed Sep 20, 2026
- Last push (Eigenwise/atomic-agents) · observed Aug 16, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (langchain-ai/langgraph) · observed Sep 20, 2026
- GitHub forks (langchain-ai/langgraph) · observed Sep 20, 2026
- Last push (langchain-ai/langgraph) · observed Sep 18, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: atomic-agents 6.2k · langgraph 42k (synced Sep 20, 2026).
Common questions
- What is the difference between atomic-agents and langgraph?
- atomic-agents: Building AI agents, atomically. langgraph: Low-level orchestration framework for building stateful agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose atomic-agents over langgraph?
- Choose atomic-agents over langgraph when Tags unique to atomic-agents: ai, artificial-intelligence, large-language-model, llms; Also covers LLM Frameworks; When you need a flexible toolkit to create atomic, modular AI agents with various LLM provider support.
- When should I choose langgraph over atomic-agents?
- Choose langgraph over atomic-agents when Tags unique to langgraph: agents, ai-agents, framework, langchain; When you need to build agents that can persist through failures and resume from where they left off, ensuring durable execution; More GitHub stars (42k vs 6.2k) - visibility, not fit.
- When should I avoid atomic-agents?
- Avoid for projects needing exclusive use of providers not listed in the Instructor docs Not suitable if looking for a solution that is language-agnostic, as it’s tightly integrated with Python ecosystems and CLI utilities
- When should I avoid langgraph?
- If you are looking for a higher-level package that simplifies the process of building agents with planning and subagent capabilities, consider Deep Agents instead. For projects that do not require long-running, stateful workflows, LangGraph's features may be overkill and a simpler framework might be more appropriate. If your project is primarily focused on JavaScript or TypeScript, LangGraph.js might be a better fit, as LangGraph is primarily designed for Python environments.
- Is atomic-agents or langgraph more popular on GitHub?
- langgraph has more GitHub stars (41,866 vs 6,185). Stars measure visibility, not whether either tool fits your constraints.
- Are atomic-agents and langgraph open source?
- Yes - both are open-source projects on GitHub (atomic-agents: MIT, langgraph: MIT).
- Where can I find alternatives to atomic-agents or langgraph?
- GraphCanon lists graph-backed alternatives at atomic-agents alternatives and langgraph alternatives (atomic-agents markdown twin, langgraph 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, atomic-agents or langgraph?
- atomic-agents: Very active. langgraph: 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 atomic-agents and langgraph?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: atomic-agents trust report; langgraph trust report.