REST vs GraphQL vs MCP: A 5-Minute Breakdown

Three patterns, three jobs. Most teams will use at least two.

REST in one paragraph

Resources are nouns. Verbs are HTTP methods. URLs map to data. GET /users/42 returns user 42. Predictable, cacheable, and the default style for most public APIs. Best when your data model is well-defined and your clients are diverse.

GraphQL in one paragraph

One endpoint. Clients send a query that names exactly the fields they want. Server returns a JSON tree that matches. Solves over-fetching and the N+1 round-trip problem REST has on complex UIs. Costs you caching simplicity and adds schema maintenance. Best when one team owns both the API and the front-ends and the data graph is dense.

MCP in one paragraph

A protocol for AI models to discover and call tools. Server exposes named tools with JSON-Schema parameters and human-readable descriptions. Client (an AI model) decides which one to call. Best when the consumer is an LLM and you want it to make decisions about which operation to run.

Side by side

	REST	GraphQL	MCP
Primary consumer	Any program	Front-end apps	AI models
Schema	OpenAPI	SDL	JSON Schema per tool
Discovery	Static docs	Introspection	Runtime listing
Caching	HTTP-native	App-level	Not really
Best at	Public APIs	Complex UIs	AI tool surfaces
Maturity	Decades	~10 years	<2 years

Which to pick

You'll usually have:

• REST as the system-of-record API
• GraphQL on top, optionally, if your front-end's data needs are gnarly
• MCP on top of REST, when you want AI to use the same operations your apps do

These layers don't fight each other. They serve different callers.

Test all three the same way

If your stack has more than one of these, you don't want three testing tools. PreMan handles REST, GraphQL, and MCP in the same workspace, with one auth model and one history. One paste, one run, one log of what actually happened.

→ Try all three in PreMan