Updated 2026年4月

LangGraph for Multi-Agent Systems

LangChain · MIT · primary language python · token-overhead ×1.0

15-axis capability scores

  • Sequential workflows9/10
  • Parallel workflows9/10
  • Hierarchical workflows9/10
  • Adaptive workflows10/10
  • State management10/10
  • Human-in-the-loop10/10
  • Python support10/10
  • TypeScript support8/10
  • .NET / Java support0/10
  • MCP support7/10
  • A2A support5/10
  • Observability10/10
  • Deployment flexibility9/10
  • Maturity9/10
  • Learning curve (higher = easier)5/10

Tokens per task

LangGraph 相对于 1.0 基线（LangGraph）具有 ×1.0 的 token 开销系数。对于每月 50,000 个任务、15,000 个基础 token 的工作负载，在 HITL 或多智能体扇出之前大约是 每月 750.0M token。

运行向导以根据您的工作负载和所选模型获得校准估算。

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Starter scaffold

Buzzi 为 LangGraph 提供 2 智能体 hello-world ZIP（Dockerfile、锁定依赖、README、MIT 许可证）。完成向导时生成。

Closest alternatives

Ready to commit to LangGraph?

Run the wizard, download the scaffold, and book a 30-minute scoping call with Buzzi.ai.

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