MCP vs REST API vs function calling: which one should you use?
"Should we just use MCP for this?" We hear that a lot. The honest answer is: sometimes. REST, OpenAPI, function calling and MCP solve different problems, and plenty of good systems use more than one.
The comparison
| Option | What it is | Pick it when | Watch out for |
|---|---|---|---|
| REST API | A resource-style HTTP interface | Any client needs a stable public contract | Not built for models to discover tools |
| OpenAPI | A description of an HTTP API | You want docs, generated clients, contract tests | It describes an API. It isn't a runtime protocol for AI apps |
| Function calling | A model feature: the model names a function and arguments, your code runs it | One app, a small fixed set of functions | The functions are baked into that one app |
| MCP | A protocol so any compatible host can find and call a server's tools | Several AI apps need the same capability | One more thing to secure, version and run |
| Agent framework | A library to orchestrate model calls, memory and steps | You're building the host side | Not a protocol. It may or may not speak MCP |
| Direct SDK call | Using a vendor SDK in your code | The integration is fixed and you own the code | You rebuild it for every app that needs it |
They work together
A very common setup: an MCP server wraps a REST API. The tool validates the input, calls the API with a locked-down credential, and sends back a trimmed result. The AI app might use function calling internally to decide when to call that tool. An agent framework can sit in the middle as the MCP client. Nobody is replacing anybody.
One question that settles most cases
Who else, apart from my own code, needs to call this?
- "Other AI apps I don't control" → MCP is worth it.
- "Nobody" → skip it. A normal API call or function calling will do.
Quick scenarios
| Situation | Start with |
|---|---|
| One web app calls one internal service with a fixed contract | REST or gRPC and a normal client library |
| You need public, cacheable HTTP endpoints | REST with OpenAPI docs |
| Several AI apps must discover and use your capability | An MCP server |
| A model needs two or three functions inside one app you own | Plain function calling |
This is our own guidance, based on the MCP spec and ordinary engineering practice. Your constraints may differ.
Read next
- New to the protocol? What is MCP?
- Try it: the Python MCP server tutorial
- The full decision tables, diagrams and tested code live in the MCP Builder's Handbook.
Frequently asked questions
Does MCP replace REST APIs?
No. They sit at different layers. An MCP server often wraps a REST API, adds validation and a least-privilege credential, and returns a trimmed result.
Is function calling the same as MCP?
No. Function calling is a model feature: the model names a function and arguments, and your code runs it. MCP is a protocol that lets any compatible app discover and call a server's tools.
When is MCP the right choice?
When several AI apps, or your users' own AI tools, need the same capability and you want a clear boundary around what they're allowed to do.