If you are a .NET shop on Azure, the Microsoft stack is the pragmatic choice, but start new agent projects on the Microsoft Agent Framework rather than Semantic Kernel itself, since that is where Microsoft's development effort now goes. Existing Semantic Kernel apps remain supported and migration is manageable. Python-first teams without Azure ties have lighter options.
What is Microsoft Semantic Kernel?
Semantic Kernel is Microsoft's open-source SDK for integrating LLMs into applications, with a kernel-and-plugins model, planners, and agent abstractions, and it is notable as the main first-class option for .NET and Java teams. In 2026 Microsoft shipped the Microsoft Agent Framework 1.0, which merges Semantic Kernel and AutoGen into a single successor SDK, positioning Semantic Kernel itself in maintenance mode for new agent work. It remains widely deployed in enterprises, especially those already on Azure.
Best for
Enterprise .NET and Java teams, especially on Azure, who want a Microsoft-supported path for LLM features and agents.
Not for
Teams starting greenfield agent projects who are not tied to .NET or Azure, or anyone wanting a minimal framework.
Strengths
- First-class C#/.NET support, which most agent frameworks lack, plus Python and Java
- Enterprise features like dependency injection, telemetry, and filters fit existing Microsoft stacks
- Deep integration with Azure OpenAI and the wider Azure ecosystem
- Mature abstractions for plugins, embeddings, vector stores, and RAG
- Clear, supported migration path to the Microsoft Agent Framework, typically a few hours for a typical app
- Backed by Microsoft with enterprise support options
Limitations
- Superseded for new agent development by the Microsoft Agent Framework, so its long-term role is legacy support
- History of significant API churn and renamed concepts across versions, so older tutorials mislead
- Heavier and more ceremony-laden than lightweight frameworks for simple use cases
- Most natural on Azure and OpenAI models, with other providers less first-class
- Multi-agent fan-out can hit Azure OpenAI rate limits quickly at scale without careful design
Microsoft Semantic Kernel pricing
Free open-source SDK; Microsoft monetizes through Azure consumption, model usage, and hosting rather than the framework.
Pricing reflects public plans as of July 2, 2026 and can change. Check Microsoft Semantic Kernel for the latest.
Microsoft Semantic Kernel FAQ
Is Semantic Kernel deprecated?
Not deprecated, but superseded for new agent work. Microsoft shipped the Microsoft Agent Framework 1.0 in 2026 as the unification of Semantic Kernel and AutoGen, and recommends it for new projects. Semantic Kernel continues to receive support, and migration for a typical app is on the order of hours, not weeks.
Semantic Kernel vs LangChain?
Semantic Kernel is the natural pick for .NET and Java teams and for organizations standardized on Azure, with enterprise patterns built in. LangChain has the bigger ecosystem and is Python/JavaScript-first. If you write C#, Semantic Kernel or its Agent Framework successor is effectively the default; in Python the choice is more contested.
Is Semantic Kernel free?
Yes, it is MIT-licensed open source with no license fee. Costs come from the model APIs you call, usually Azure OpenAI, and your hosting.
What is the Microsoft Agent Framework?
It is Microsoft's successor SDK that merges Semantic Kernel's enterprise features with AutoGen's agent and orchestration ideas into one framework for .NET and Python, reaching 1.0 in 2026. New agent projects on the Microsoft stack should generally start there.
Looking at alternatives? Semantic Kernel is a different tool for a different job, an SDK for enterprise developers embedding AI into .NET and Java systems. Autonoly handles the surrounding business workflows, giving operations teams automations they can build and change themselves while the engineering team focuses on product code. See the Autonoly review.