Updated aprile 2026
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 porta un moltiplicatore di overhead in token di ×1.2 rispetto a una baseline 1,0 (LangGraph). Per un carico di 50.000 task al mese a 15.000 token base, sono circa 900.0M token al mese prima di HITL o fan-out multi-agente.
Esegui il wizard per una stima calibrata sul tuo carico di lavoro e modello scelto.
Run the selector with your workloadStarter scaffold
Buzzi consegna uno ZIP hello-world a 2 agenti per Microsoft Semantic Kernel (Dockerfile, dipendenze fissate, README, licenza MIT). Generato al completamento del wizard.
Closest alternatives
- Google Agent Development Kit
×1.2 overhead · python
- AutoGen / AG2
×2.5 overhead · python
- Haystack
×1.3 overhead · python
Ready to commit to Microsoft Semantic Kernel?
Run the wizard, download the scaffold, and book a 30-minute scoping call with Buzzi.ai.
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