Updated 2026年4月
Microsoft Semantic Kernel for Multi-Agent Systems
Microsoft · MIT · primary language multi · token-overhead ×1.2
15-axis capability scores
- Sequential workflows8/10
- Parallel workflows7/10
- Hierarchical workflows8/10
- Adaptive workflows7/10
- State management8/10
- Human-in-the-loop7/10
- Python support8/10
- TypeScript support0/10
- .NET / Java support10/10
- MCP support7/10
- A2A support5/10
- Observability9/10
- Deployment flexibility9/10
- Maturity8/10
- Learning curve (higher = easier)6/10
Tokens per task
Microsoft Semantic Kernel 相对于 1.0 基线（LangGraph）具有 ×1.2 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 900.0M 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。
Run the selector with your workloadStarter scaffold
Buzzi 为 Microsoft Semantic Kernel 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
- Google Agent Development Kit
×1.2 overhead · python
- AutoGen / AG2
×2.5 overhead · python
- Haystack
×1.3 overhead · python
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Run the wizard, download the scaffold, and book a 30-minute scoping call with Buzzi.ai.
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