MCP vs. API: Key Differences and When To Use Each

APIs and the Model Context Protocol (MCP) address different integration needs: APIs provide fixed, documented endpoints for deterministic software-to-software data exchange, while MCP, introduced by Anthropic in 2024, lets AI agents dynamically discover and invoke available tools through a standardized client-server protocol. APIs generally use HTTP, predefined schemas, and credentials such as API keys or OAuth, whereas MCP uses JSON-RPC, runtime tool discovery, session-based context, and OAuth 2.1 or environment-based authentication. The two are often layered together, with MCP enabling an agent to select tools based on a prompt while underlying APIs perform the actual service calls, validation, and rate limiting. Direct APIs are suited to predictable workflows such as scheduled data synchronization, while MCP is useful when an agent must adapt its sequence of actions, such as investigating a customer complaint or determining refund eligibility. The workflow platform n8n supports both approaches through HTTP request tools, MCP client connections, and MCP server triggers that expose workflows as agent-callable tools, allowing deterministic sub-workflows and agent-driven decisions to coexist.

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