Comparisons / Mastra vs Semantic Kernel

Mastra vs Semantic Kernel: Which Agent Framework to Use?

Mastra vs Semantic Kernel, head to head

Mastra and Semantic Kernel both let you build an agent, but they sit in different parts of the stack and they assume different things about who's writing the code.

Mastra is a TypeScript-first framework for building AI agents, from the team behind Gatsby.

Semantic Kernel is Microsoft's enterprise SDK for building AI agents.

Underneath, both wrap the same thing: a model call, a tool dispatch, a loop. The decision is about which abstraction your team wants to think in day to day, and which ecosystem you're willing to inherit along with it. There's an honest, framework-free version of the same pattern in about 60 lines of Python in the lesson at the bottom of this page — useful as a baseline regardless of which framework wins.

Pick Mastra if

Pick Mastra if mastra is the best option for TypeScript teams that want a batteries-included agent framework without leaving the Node.js ecosystem. The workflow engine and Studio are genuinely productive. For simple agents or Python teams, the plain approach avoids an unnecessary dependency. The tradeoffs in its intro should match how your team already thinks about agents; Semantic Kernel will feel like translation if they don't.

Full Mastracomparison →

Pick Semantic Kernel if

Pick Semantic Kernel if semantic Kernel earns its complexity in enterprise environments with Azure OpenAI, .NET backends, and existing Microsoft infrastructure. But the core agent pattern — LLM call, tool dispatch, loop — is identical to what you can build in 60 lines of Python. The tradeoffs in its intro should match how your team already thinks about agents; Mastra will feel like translation if they don't.

Full Semantic Kernelcomparison →

What both add

Whichever you pick, you're inheriting a dependency tree and a vocabulary your team has to learn before they ship anything. Mastra has its own class hierarchy and tool registration conventions; Semantic Kernel has its. Either way, when something misbehaves you'll be reading framework source before you reach the actual HTTP call.

If the real workload is one model and a handful of tools, both can feel like a workbench for driving a nail. The lesson below builds the same pattern in plain Python — useful as a comparison point even if you ultimately keep the framework.

By the numbers

By the numbers

Mastra

GitHub Stars

22.7k

Forks

1.8k

Language

TypeScript

License

Apache-2.0

Created

2024-08-06

Created by

Mastra AI

Backed by

Spark Capital, Y Combinator

Funding

Series A ($22M, Apr 2026 — $35M total)

Weekly downloads

244.0k

github.com/mastra-ai/mastra

Semantic Kernel

GitHub Stars

27.6k

Forks

4.5k

Language

C#

License

MIT

Created

2023-02-27

Created by

Microsoft

github.com/microsoft/semantic-kernel

GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.

ConceptMastraSemantic Kernel
Agent`new Agent({ model, instructions, tools })` with automatic tool dispatch`ChatCompletionAgent` with `Kernel`, instructions, and service config
Tools`createTool({ name, schema, execute })` with Zod validation
Workflows`Workflow` class with `.step()`, `.then()`, `.branch()` for orchestration
RAGBuilt-in document syncing, chunking, embedding, and vector search
MemoryShort-term thread memory + long-term vector memory across sessions`SemanticTextMemory` with embeddings and vector stores
StudioMastra Studio: local GUI for testing agents, viewing traces, debugging
Tools / Plugins`KernelPlugin` with `@kernel_function` decorators, typed parameters
Planning`StepwisePlanner`, `HandlebarsPlanner` for multi-step decomposition
Orchestration`Kernel.invoke()` with plugin resolution and filter pipeline
Multi-LanguageC#, Python, Java SDKs with shared abstractions

Or build your own in 60 lines

Both Mastra and Semantic Kernel implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.

No framework. No dependencies. No opinions. Just the code.

Build it from scratch →