Microsoft Agent Framework vs Semantic Kernel
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A Microsoft framework for building and running AI agents and multi-agent workflows in Python and .NET.
Open source · MIT
Open-source SDK for building AI agents and multi-agent apps in Python, .NET and Java.
The short answer
Choose Microsoft Agent Framework if you need…
- Developers building agents or multi-agent workflows they plan to run in production
- Teams that need orchestration beyond a single prompt or stateless chat loop
- Python or C#/.NET developers who want one framework across both languages
- Teams that want to switch model providers without rewriting their architecture
Choose Semantic Kernel if you need…
- Developers already using Azure OpenAI or OpenAI who want a structured SDK for agents
- Teams working in .NET, Python or Java who want one framework across languages
- Projects that need plugins built from native code, prompt templates, OpenAPI specs or MCP
- Existing Semantic Kernel users maintaining or migrating older code
Side-by-side
| Microsoft Agent Framework | Semantic Kernel | |
|---|---|---|
| Type | Library | Library |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 14.5k | 28.7k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Install with a package manager | Install with a package manager |
| Main language | Python | C# |
| Last code update | 4 days ago | 4 days ago |
What each one is
Microsoft Agent Framework
Microsoft Agent Framework is a set of code libraries for building AI agents, which are programs that use language models to carry out tasks, and for connecting several agents into workflows. It supports Python and .NET with similar APIs, and includes features such as orchestration patterns, middleware, OpenTelemetry tracing, and a developer UI. Developers use it to move agent prototypes toward production with an approach that is not tied to a single model provider.
Semantic Kernel
Semantic Kernel is a model-agnostic SDK from Microsoft that lets developers connect large language models (such as OpenAI or Azure OpenAI models) to their own apps, add tools and plugins, and orchestrate one or more AI agents. The README says it is now succeeded by Microsoft Agent Framework, so new projects should check that project first.
Best for
Microsoft Agent Framework
- Developers building agents or multi-agent workflows they plan to run in production
- Teams that need orchestration beyond a single prompt or stateless chat loop
- Python or C#/.NET developers who want one framework across both languages
- Teams that want to switch model providers without rewriting their architecture
- Developers who use Microsoft Foundry or Azure OpenAI
Semantic Kernel
- Developers already using Azure OpenAI or OpenAI who want a structured SDK for agents
- Teams working in .NET, Python or Java who want one framework across languages
- Projects that need plugins built from native code, prompt templates, OpenAPI specs or MCP
- Existing Semantic Kernel users maintaining or migrating older code
Strengths
Microsoft Agent Framework
- Supports both Python and .NET with documented samples for each
- Includes built-in OpenTelemetry observability and middleware for custom request handling
- Offers graph-based orchestration patterns and provider flexibility in one framework
Semantic Kernel
- Supports several models and providers, including OpenAI, Azure OpenAI, Hugging Face and NVidia, per the README
- Offers examples in Python and C# with matching quickstarts
- Permissive MIT license and a large public project with about 28,700 stars
Not ideal for
Microsoft Agent Framework
- People who only want a simple chatbot or a single prompt call; the framework is built for multi-step orchestration and may be more than needed
- Non-developers, since setup requires writing code and configuring cloud credentials
- Teams that need Go support from this repo; the README says Go lives in a separate repository, microsoft/agent-framework-go
Semantic Kernel
- Non-programmers: it is a developer SDK and needs code to use, so no-code users should look elsewhere
- Teams starting fresh who want the newest path: the README directs users to Microsoft Agent Framework as the successor
- Simple scripts that only need one direct API call, where an SDK adds more structure than needed
Trade-offs
Microsoft Agent Framework
- The README is truncated and several features, such as time-travel and the Labs packages, are described only briefly, so details need checking in the docs
- Quickstarts assume Azure and Microsoft Foundry access, which may be a barrier outside that ecosystem
- Some components are marked experimental (AF Labs), so stability varies by package
Semantic Kernel
- The README states the project is succeeded by Microsoft Agent Framework, so long-term direction may point elsewhere
- Quickstarts assume Azure or OpenAI credentials and a configured environment, so setup needs some engineering work
- Java support is pointed to a separate build guide rather than documented here
Getting started
Microsoft Agent Framework
Install the Python package
pip install agent-frameworkAdd the .NET core package
dotnet add package Microsoft.Agents.AISemantic Kernel
Set Azure OpenAI API key
export AZURE_OPENAI_API_KEY=AAA....Set OpenAI API key (alternative)
export OPENAI_API_KEY=sk-...Frequently asked questions
What is the difference between Microsoft Agent Framework and Semantic Kernel?
Microsoft Agent Framework: A Microsoft framework for building and running AI agents and multi-agent workflows in Python and .NET. Semantic Kernel: Open-source SDK for building AI agents and multi-agent apps in Python, .NET and Java. Microsoft Agent Framework suits developers building agents or multi-agent workflows they plan to run in production, while Semantic Kernel suits developers already using azure openai or openai who want a structured sdk for agents.
Are Microsoft Agent Framework and Semantic Kernel free?
Microsoft Agent Framework: Free and open source. Semantic Kernel: Free and open source.
Is Microsoft Agent Framework or Semantic Kernel more popular?
Semantic Kernel has more GitHub stars (28.7k) than Microsoft Agent Framework (14.5k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to Microsoft Agent Framework and Semantic Kernel?
Other options people compare them with include LangGraph, CrewAI, PageIndex, PocketFlow, OpenAI Agents SDK.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.