Semantic Kernel vs Microsoft Agent Framework
Compare Microsoft AI orchestration options for enterprise application integration and agent workflow development.
Semantic Kernel
Microsoft SDK for integrating AI orchestration, plugins, agents, and enterprise application workflows.
Microsoft Agent Framework
Microsoft framework for building, orchestrating, and deploying agents and multi-agent workflows across Python and .NET.
Recommendation
Use Semantic Kernel when plugin-based AI application integration is central. Use Microsoft Agent Framework when agent and multi-agent workflow orchestration is the main product shape.
Comparison criteria
Decision matrix
| Criterion | Semantic Kernel | Microsoft Agent Framework | Winner | Summary |
|---|---|---|---|---|
| Enterprise integration | Strong fit for integrating AI into existing applications through plugins and orchestration. | Strong fit for building agent workflows across Python and .NET. | depends | Choose by whether app integration or agent workflow is the main shape. |
| Agent workflow | Agent-oriented features exist in the Microsoft AI stack. | Explicitly tracked as a framework for agent and multi-agent workflows. | right | Microsoft Agent Framework has the clearer agent-workflow identity. |
| Language support | C#, Python, and Java are represented in the graph. | Python and .NET are represented in the graph. | left | Semantic Kernel has broader language coverage in this graph. |
| Deployment fit | Tracked for server, container, and workflow runtime deployment. | Tracked for server, container, and workflow runtime deployment. | tie | Both need deployment-specific validation. |
Related compatibility facts
| Source | Target | Status | Evidence |
|---|---|---|---|
| microsoft-agent-framework | github-mcp-server | verify_required | Agent Framework can orchestrate tool-using agents, while GitHub MCP Server exposes repository tools through MCP; integration should be verified per host and transport. |
| microsoft-agent-framework | serverless-container-runtime | supported | Agent Framework targets production-grade agent and workflow deployments that fit server and container runtime patterns. |
| semantic-kernel | serverless-container-runtime | verify_required | Semantic Kernel can run in application services and containerized enterprise stacks, but language runtime and connector dependencies must be validated. |
What makes an agent stack enterprise-ready?
An enterprise-ready stack should expose governance boundaries, source verification, observability, host compatibility, and deployment paths that match existing platform and language constraints.
What is the difference between Semantic Kernel and Microsoft Agent Framework?
Semantic Kernel is a strong fit for plugin-based AI application integration, while Microsoft Agent Framework is the clearer fit for agent and multi-agent workflow orchestration.