JSON-RPC vs REST and why JSON-RPC is used in MCP?

I was going down the rabbit hole of MCP protocol details and realised that it was using JSON-RPC instead of REST. 

JSON-RPC is a simple protocol that lets a program on one computer run a function on another computer. It uses JSON to send and receive the requests and responses, making it easy to use and understand.

It is transport-agnostic and can work over HTTP, TCP, sockets, or other message-passing environments. A JSON-RPC request typically includes the method to be called, parameters for that method (optional), and an ID to match the response.

Given below is a simple example of a request and response:

Given below are the top 3 differences in JSON-RPC vs REST for API design:

Architecture Style:

• JSON-RPC: RPC-oriented, focusing on invoking specific methods or procedures on the server (e.g., calling a function like getBalance()). It treats interactions as direct commands.
• REST: Resource-oriented, centered on manipulating resources (e.g., /users/{id}) using standard HTTP methods like GET, POST, PUT, and DELETE.

Endpoints and HTTP Methods:

• JSON-RPC: Uses a single endpoint (e.g., /rpc) with POST requests for all method calls, simplifying routing but limiting HTTP verb usage.
• REST: Employs multiple endpoints (e.g., /users, /orders) and leverages various HTTP methods (GET, POST, PUT, DELETE) to represent different actions on resources.

Request/Response Structure:

• JSON-RPC: Requests and responses follow a strict JSON format with fields like "method", "params", "id", and "result" or "error". Supports batching natively.
• REST: Uses flexible request formats (URL paths, query parameters, headers) and responses rely on HTTP status codes (e.g., 200, 404) with custom payloads; batching requires custom implementation.

MCP chose JSON-RPC because its lightweight, single-endpoint design ensures fast and efficient communication for real-time AI tasks. It supports batch requests, allowing multiple operations in one call, which suits MCP’s complex AI workflows.