Agent vs langgraph
Side-by-side comparison of two AI agent tools
Short answer
- langgraph is growing faster: +99 GitHub stars in the last 30 days vs +21 for Agent.
- Pick Agent for: create state-machine-powered LLM agents using XState. Pick langgraph for: framework to build resilient language agents as graphs.
From GitHub data refreshed daily.
Agentopen-source
Create state-machine-powered LLM agents using XState
langgraphopen-source
Framework to build resilient language agents as graphs.
Metrics
| Agent | langgraph | |
|---|---|---|
| Stars | 472 | 3.3k |
| Star velocity /mo | 20.68421052631579 | 98.52631578947368 |
| Commits (90d) | 310 | 145 |
| Releases (6m) | 10 | 10 |
| Overall score | 0.6245788355727497 | 0.6636992956489073 |
Pros
- +State machine structure provides predictable, auditable agent behavior with clear transition logic
- +Learning capabilities through observations and feedback enable agents to improve performance over time
- +Flexible model provider support via Vercel AI SDK integration allows switching between different LLMs
- +提供可视化的图形控制流，让智能体行为更加透明和可调试，相比黑盒式的自主智能体更易于理解和维护
- +内置人机协作机制和长期记忆支持，适合处理需要人工介入或持续状态的复杂业务流程
- +CLI 工具和预构建智能体模板显著降低了入门门槛，支持从概念验证到生产部署的快速迭代
Cons
- -Higher complexity compared to simple prompt-based agents, requiring knowledge of both XState and AI concepts
- -Documentation appears incomplete with placeholder sections for key setup instructions
- -State machine approach may be overkill for simple conversational agents or basic AI tasks
- -作为低级框架需要更多的架构设计工作，学习曲线相对陡峭，不如高级抽象框架那样开箱即用
- -主要依赖 LangChain 生态系统，在非 LangChain 技术栈中的集成可能需要额外的适配工作
Use Cases
- •Customer service chatbots that need to follow specific escalation workflows and remember interaction history
- •Game AI characters that must exhibit consistent behavior patterns while adapting to player actions
- •Automated support systems requiring structured decision trees with learning from resolution outcomes
- •构建需要人工审核和批准的自动化工作流，如内容审核、财务审批或合规检查流程
- •开发具有长期记忆的客服或助理智能体，能够跨会话保持上下文和用户偏好
- •创建复杂的数据处理管道，需要在多个 AI 模型和外部 API 之间协调执行任务
FAQ
- Which is more popular, Agent or langgraph?
- langgraph has more GitHub stars (3,333 vs 472).
- Which is more actively developed, Agent or langgraph?
- Agent had more commits in the last 90 days (310 vs 145).
- Should I use Agent or langgraph?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.