Model Context Protocol: guides & tutorials

The Model Context Protocol (MCP) is the USB-C for AI: a single open standard that connects AI applications to tools, data sources, and workflows. Originated by Anthropic in late 2024 and now an open, community-maintained standard, MCP is supported across a wide range of clients (Claude Desktop and Claude Code, ChatGPT, VS Code, Cursor, and others). The specification covers two transports (local stdio and remote Streamable HTTP, which supersedes the older HTTP+SSE transport), server-side tools, resources, and prompts, and an OAuth 2.1-based authorization flow for remote servers. The public server ecosystem is large and growing fast, spanning official Anthropic servers, vendor servers, and community projects.

If you do not already use Claude, you can try Claude free for a week and follow along with every example in this handbook. The guide covers MCP server development end-to-end, from your first server to production deployment with authentication.

TL;DR:

Prerequisites:

• Node.js 18+ or Python 3.10+
• Claude Desktop or Claude Code installed
• Basic understanding of APIs and JSON

Large Language Models require synchronous access to the live web to prevent hallucination. The AI Agents collection on Apify provides the critical orchestration layer—fully managed Model Context Protocol (MCP) servers and autonomous headless browser frameworks—with the picks below biased toward agents that already see real execution volume.

Large language models have no native access to the outside world. On their own they cannot read a URL, query a database, or run a tool. Historically, bridging a model to live internet data meant writing brittle per-framework glue (LangChain tool definitions mapping to REST endpoints, and a different wrapper for the next framework).

The Model Context Protocol (MCP) standardizes that boundary. Anthropic introduced it in November 2024, and it is now an open standard that hosts like Claude, Cursor, and VS Code all speak. Think of it as a USB-C port for AI applications: one connector, many tools.

This guide walks through the mechanics of MCP and a worked setup that connects the Apify MCP server so an AI client can reach the live web by running Apify Actors.