MCP vs REST: Why AI Assistants Need More Than Your Existing API Endpoints
REST APIs are built for deterministic callers like scripts and pipelines that already know the exact routes, headers, and parameters to use. AI assistants such as ChatGPT and Claude, however, start from a user's natural language request and require named tools, descriptions, input schemas, and permission boundaries to act reliably. Model Context Protocol (MCP) provides this structured contract on top of existing domain logic, enabling assistants to discover and safely invoke capabilities without guessing URLs or asking users to paste curl commands. MCP introduces three key constructs — Tools, Resources, and Prompts — that map to underlying HTTP calls while shielding the model from private API internals. Developers are advised to layer both approaches, keeping REST for automation and CI while exposing a separate MCP surface for assistant-facing interactions, rather than replacing one with the other.
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