Mastra vs Semantic Kernel (2026)
Updated March 10, 2026
Overview
Mastra is a TypeScript-first agent framework for building production AI applications. It provides primitives for agents, workflows, RAG, integrations, and memory with a focus on developer experience and type safety. Mastra is designed for full-stack TypeScript developers who want to build AI features without leaving their existing tech stack.
Semantic Kernel is Microsoft's enterprise SDK for integrating AI into applications. It provides planners for multi-step task execution, plugin architectures for tool use, memory systems, and connectors for all major LLM providers. Available in C#, Python, and Java, Semantic Kernel is designed for enterprise .NET shops building AI-powered features into existing applications.
Key features
Core capabilities each platform advertises.
- TypeScript agent framework
- Built-in tool calling and workflows
- Sync engine for agent state
- Integration marketplace
- Production-ready agent primitives
- Enterprise AI orchestration by Microsoft
- C# and Python SDKs
- Plugin architecture for tools
- Memory and planning capabilities
- Azure and Microsoft 365 integration
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Production-ready platform
- Good performance
- Active development
- Strong features
Cons
- Enterprise pricing varies
- Setup complexity
- Learning curve required
Pros
- Free open-source
- Microsoft-backed
- Multi-language
Cons
- Learning curve
- Microsoft focus
Mastra or Semantic Kernel — which should you choose?
Choose Mastra if you wantChoose if you want
- TypeScript-native agent development
- Building AI workflows with tool use
- Agent state management
- Production agent deployment
- Multi-step task automation
Choose Semantic Kernel if you wantChoose if you want
- Enterprise AI on Microsoft stack
- Copilot-style applications
- Integrating AI into .NET applications
- Microsoft 365 automation
- Enterprise workflow orchestration
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