import {
DocsTitle,
DocsLead,
DocsH2,
DocsP,
DocsList,
DocsLi,
DocsCode,
Mono,
} from '@/components/docs-page';
export const metadata = { title: 'MCP concepts — BuildMyMCPServer docs' };
export default function Concepts() {
return (
<>
MCP concepts
Model Context Protocol is an open standard from Anthropic for connecting AI assistants to
external tools, data, and APIs. Three primitives, one transport.
The three primitives
Tools — functions the AI can invoke.
Each has a name, a description, an input schema (JSON Schema or Zod), and a server-side
implementation. The AI decides when to call them based on the description.
Resources — read-only data the AI can
fetch. URI-addressed. Think files, documents, database records.
Prompts — parameterized prompt templates
the server exposes to the client. Used for orchestration patterns the server author
wants to encourage.
Transport: Streamable HTTP
Every generated server speaks Streamable HTTP (MCP spec 2025-11-25). The
previous SSE transport was deprecated in June 2025 and is not supported here. One HTTP
endpoint at /mcp, optionally negotiating a long-lived stream via
text/event-stream when the server wants to push updates.
Content-Type: application/json
Accept: application/json, text/event-stream
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/list"
}`}
/>
Session lifecycle
initialize — client sends protocol version + capabilities, server returns
its info and assigns a session id via the mcp-session-id header.
notifications/initialized — client confirms readiness. Server is now free
to push notifications.
tools/list, tools/call, resources/list,
prompts/list — the work.
Why MCP and not just REST
REST APIs need bespoke OpenAPI integration per client. MCP standardizes the discovery,
invocation, auth and streaming so any spec-compliant client picks up any spec-compliant
server with zero glue code. That's the entire point.
>
);
}