MCP vs API
MCP doesn't replace APIs — it sits on top of them. An API exposes a product's functionality to developers who write code against it; an MCP server re-exposes that same functionality to AI models in a self-describing format they can discover and call at runtime. Nearly every MCP server is a thin wrapper around the vendor's existing API.
Side by side
| API (REST, GraphQL…) | MCP | |
|---|---|---|
| Built for | Developers writing code | AI models choosing actions at runtime |
| Discovery | A human reads the docs | The client asks tools/list, gets typed schemas back |
| Interface shape | Different per product — endpoints, verbs, conventions | Uniform — JSON-RPC 2.0 tools, same shape for every product |
| Integration cost | One integration per app-and-product pair | One server per product; every MCP client can use it |
| Handling change | Breaking changes mean code updates downstream | Clients re-discover the tool list every session |
| Auth | Per-API keys and OAuth flows, wired by each integrator | OAuth standardized in the protocol for remote servers |
When to use which
Building software that talks to a product? Use its API — MCP would add a layer you don't need, and APIs remain the contract with the best performance and control.
Giving an AI assistant access to a product? Use its MCP server if one exists — check here first — because the discovery, schemas and auth come solved, and the same setup works in Claude, Cursor, ChatGPT and the rest.
Vendor deciding whether to ship one? It's not either/or: the MCP server is a thin layer over the API you already run, and it's rapidly becoming the difference between assistants that can use your product and assistants that can only describe it.
Common questions
Does MCP replace REST APIs?
No. Nearly every MCP server is a wrapper around an existing API — the API keeps doing the actual work. MCP replaces the per-app glue code between AI assistants and those APIs, not the APIs themselves.
Is MCP itself an API?
Technically yes — it's a JSON-RPC 2.0 interface over stdio or HTTP. The useful distinction is the consumer: a product API is designed for developers writing code against documentation; MCP is designed for AI models discovering capabilities at runtime.
Can an AI assistant use a plain API without MCP?
Yes, through custom function calling: you describe each endpoint to the model and write the execution code yourself. That works fine inside one app — but the work repeats for every app and every API, which is exactly the multiplication MCP exists to remove.
If I already have an API, how much work is an MCP server?
Small, as integrations go. Official SDKs exist for the major languages, and a basic server is a thin translation layer: one tool definition per capability you want to expose, delegating to the API you already run.
More pairings: the compare hub · protocol basics: What is MCP?