MCP vs REST API — What's Different? Complete Developer Comparison (2026)

The Key Difference in One Sentence

REST APIs are designed for traditional software clients. MCP is designed for AI agents.

REST assumes the client is a developer-written program that knows exactly which endpoint to call and what parameters to pass. MCP assumes the client is an LLM — one that needs to discover what capabilities are available, reason about which to use, and maintain context across multiple steps of a task.

Side-by-Side Comparison

Protocol & Transport

REST communicates using standard HTTP verbs:

# REST — you call a specific URL with an HTTP verb
GET  /users/123           → fetch user
POST /users               → create user
PUT  /users/123           → update user
DELETE /users/123         → delete user

MCP communicates using JSON-RPC 2.0 — a method-call pattern sent over HTTP (streaming) or STDIO:

// MCP — you call methods on a connection
→ { "method": "tools/list" }                     // discover available tools
→ { "method": "tools/call", "params": {          // call a specific tool
     "name": "get_user",
     "arguments": { "id": "123" }
   }}
→ { "method": "resources/list" }                 // list readable resources

The critical difference: the LLM discovers what tools are available at runtime by calling tools/list. With REST, the client developer reads the OpenAPI docs and hardcodes the calls. MCP is self-describing for AI.

Stateful vs Stateless

REST is stateless — every request carries all the context it needs. The server doesn't remember previous requests:

# Each REST call is independent
GET /orders?user_id=123&status=pending   # must re-send user context every time

MCP is stateful — the session maintains context across multiple tool calls. When Claude is working on a multi-step task (e.g., "find all open PRs, summarize them, then close the stale ones"), MCP tracks the session state so each step can build on the last:

// MCP session — context is preserved
Session established → Claude calls list_pull_requests
                   → Claude calls summarize_pr for each
                   → Claude calls close_pr for stale ones
                   // No need to re-authenticate or re-send context each time

Tools, Resources & Prompts vs Endpoints

REST has one primitive: endpoints. MCP has three distinct primitives, each optimized for different AI interaction patterns:

Tools are described with full JSON Schema, so the LLM knows exactly what inputs are required, their types, and what the output will look like — before it even makes the call.

When to Use REST vs MCP

MCP Wraps REST — They're Complementary

MCP doesn't replace your REST API. In practice, MCP servers are thin wrappers around existing REST APIs that make them AI-friendly. Your REST API handles the actual business logic; MCP provides the AI-native discovery and session layer on top.

// Your existing REST API (unchanged)
app.post('/api/create-issue', authenticate, async (req, res) => {
  const issue = await db.issues.create(req.body);
  res.json(issue);
});

// MCP wrapper — calls your REST API under the hood
server.tool("create_issue", {
  title: z.string(),
  description: z.string(),
  priority: z.enum(["low", "medium", "high"])
}, async ({ title, description, priority }) => {
  const response = await fetch('https://yourapp.com/api/create-issue', {
    method: 'POST',
    headers: { Authorization: `Bearer ${process.env.API_KEY}` },
    body: JSON.stringify({ title, description, priority })
  });
  const issue = await response.json();
  return { content: [{ type: "text", text: `Created issue #${issue.id}: ${title}` }] };
});

This is exactly how all the major MCP servers work — GitHub MCP wraps the GitHub REST API, Supabase MCP wraps the Supabase REST/PostgREST API, Stripe MCP wraps the Stripe REST API. MCP is the AI translation layer, not a replacement.

Frequently Asked Questions

Related Guides

• What Is the Model Context Protocol (MCP)?
• Claude MCP Apps — Full Guide
• MCP vs Function Calling vs API — Full Comparison
• Build Your First MCP Server with Python and FastMCP