Azure Functions is extending its serverless model to AI agents, letting developers define agents in markdown files with YAML-based triggers and managed execution. The preview also includes MCP server access and more than 1,400 connectors.
The practical appeal is deployment simplicity. Instead of wiring a separate agent platform, teams can package agent behavior into a familiar serverless workflow with sandboxing and existing consumption-based billing.
The release shows cloud platforms turning agent orchestration into a first-class application runtime rather than a custom framework layer.