Semantic Kernel
Lightweight open-source SDK for building AI agents and orchestrating AI models with existing code.
Data verified Sep 5, 2026
Score
About Semantic Kernel
Semantic Kernel is a lightweight, open-source development kit that lets developers build AI agents and integrate AI models into C#, Python, or Java codebases. It acts as middleware that translates AI model requests into function calls against your existing code and passes results back, combining prompts with existing APIs to automate business processes. It offers connectors to AI services, a plugin system based on OpenAPI specifications, planners, and memory abstractions for building enterprise-grade AI solutions.
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Commonly Cited Strengths & Limitations
Strengths
- Flexible, modular, and observable
- Version 1.0+ support across C#, Python, and Java
- Committed to non-breaking changes
- Lightweight and open-source
- Future proof, easily swaps in new AI models
Limitations
- Frequent breaking changes across the skills-to-plugins-to-agents evolution made long-lived codebases expensive to maintain
- Python and Java support lags the C# implementation
- Requires writing your own multi-agent orchestration logic rather than offering ready-made patterns
- Smaller community and fewer resources than more established frameworks
- Documentation can be insufficient for complex implementations
Common Use Cases
- Building AI agents
- Automating business processes
- Integrating AI models into existing codebases
Details
- Pricing Model
- Free
- Category
- Developer Tools
Who is Semantic Kernel for?
C#, Python, and Java Developers
Integrate the latest AI models into their existing codebase to build agents that call functions to perform actions.
Enterprise Developers
Deliver enterprise-grade, responsible AI solutions at scale using telemetry, hooks, and filters.
Low-code Developers
Share extensions built with OpenAPI specifications across pro and low-code developers in their company.
Frequently Asked Questions
Is Semantic Kernel free?
Yes, Semantic Kernel is free to use.
Does Semantic Kernel have an API?
Yes, Semantic Kernel provides an API for developers.
Is Semantic Kernel open source?
Yes, Semantic Kernel is open source.
What does Semantic Kernel integrate with?
Semantic Kernel integrates with OpenAPI, Microsoft 365 Copilot.
What are the downsides of Semantic Kernel?
Frequent breaking changes across the skills-to-plugins-to-agents evolution made long-lived codebases expensive to maintain Also, Python and Java support lags the C# implementation
Who is Semantic Kernel best for?
Semantic Kernel is best suited for C#, Python, and Java Developers, Enterprise Developers, Low-code Developers.
What can I use Semantic Kernel for?
Common uses for Semantic Kernel include building ai agents, automating business processes, integrating ai models into existing codebases.
How does Semantic Kernel compare to IBM API Connect?
Semantic Kernel and IBM API Connect are both used for developer tools -- specifically dev infrastructure tools. See the full side-by-side comparison for pricing and feature differences.
Key Features
- AI agent development kitLets you build AI agents and integrate the latest AI models into your C#, Python, or Java codebase.
- Enterprise readyFlexible, modular, and observable with telemetry support plus hooks and filters for responsible AI at scale.
- Function calling middlewareTranslates a model's request into a function call and passes the results back to the model.
- Business process automationCombines prompts with existing APIs so models can call your code to perform actions.
- Modular and extensible pluginsAdd your existing code as a plugin and integrate AI services through out-of-the-box connectors.
- Future proof model supportSwap in newly released AI models without rewriting your entire codebase.
- Multimodal expansionExisting chat-based APIs can be easily expanded to support voice and video.
Integrations
Technical Details
- Target Market
- B2B
- API
- Available
Support
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