API vs MCP: Which Developer Tool Wins?

Key insights

• YouTube Short summary: This short video explains Microsoft's new approach linking AI agents to APIs using Model Context Protocol (MCP) and Azure API Management.
  It highlights how MCP makes AI tools more capable and manageable for developers and enterprises.
• What MCP is: Model Context Protocol (MCP) is an open protocol that lets AI models discover and call APIs, databases, and services during execution.
  It treats those connections as standardized tools instead of ad-hoc API calls.
• Architecture and transport: MCP uses JSON-RPC 2.0 messaging and supports local stdio and networked Server-Sent Events (SSE) over HTTP.
  This design works for both local and remote AI workflows and keeps interactions consistent.
• Key advantages: MCP offers unified integration, real-time and context-aware API calls, and reusable tool interfaces for AI agents.
  It also supports enterprise features like OAuth 2.1 and Microsoft Entra ID for secure, governed access.
• Azure API Management integration: Azure API Management (APIM) (v2 preview) can expose MCP servers with full lifecycle policies—authentication, transformations, caching, and rate limits.
  APIM also adds monitoring and observability so MCP endpoints behave like managed APIs.
• Developer experience: Tools like Visual Studio Code support MCP servers (preview), letting developers add domain-specific actions for language models and share server configs.
  Microsoft and partners provide catalogs of MCP servers to speed development and integrate AI assistants into real workflows.

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