Comparisons / Mastra vs Semantic Kernel

Mastra vs Semantic Kernel: Which Agent Framework to Use?

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. Here is how they compare — paradigm, ecosystem, and the use cases each one is actually built for.

By the numbers

Mastra

GitHub Stars

22.7k

Forks

1.8k

Language

TypeScript

License

MIT

Created

2024-08-06

Created by

Mastra AI

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

Mastra vs Semantic Kernel, head to head

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

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

Both wrap the same underlying agent pattern — an LLM call, a tool dispatch, a loop — in different abstractions. The choice between them is mostly about which mental model and ecosystem fits the team you have, not which one is technically more capable.

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. Mastra is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; Semantic Kernel would force you to translate.

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. Semantic Kernel is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; Mastra would force you to translate.

Full Semantic Kernelcomparison →

What both add

Both Mastra and Semantic Kernel pull in a class hierarchy and a dependency tree to wrap what is, at the core, an HTTP POST in a while loop. If your use case is straightforward — one provider, a handful of tools, a single agent — the framework cost may exceed the framework benefit. The lesson below shows the same pattern in ~60 lines without either dependency.

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 →