MCP: Build Rich-Context AI Apps with Anthropic
For: Developers building production AI agents in 2026
Hand-reviewed courses, official docs, and tutorials for getting fluent in Claude Code. Editorial picks ordered by what we'd recommend to a friend.
Claude Code is Anthropic's terminal-native AI engineer — the closest thing in 2026 to a Unix-philosophy AI coding assistant. The reason "claude code tutorial" gets 4,400 SERP searches per month: developers coming from Cursor want the terminal alternative, and they're finding the docs alone don't close the loop on advanced workflows (sub-agents, MCP servers, hooks).
The right learning path for Claude Code: start with Anthropic's own docs and quickstart, then move to the Claude Code Cookbook for production patterns, then add 1-2 MCP servers for your specific tools (databases, internal APIs, browser automation). Most engineers underuse hooks and sub-agents — investing 2-3 hours into those alone pays back the first week.
Pair Claude Code with the MCP course on /learn/mcp once you're past the basics. The integration patterns are where the leverage compounds.
Editor-reviewed courses from our catalog that teach Claude Code or the patterns it's built on.
For: Developers building production AI agents in 2026
For: Engineers who have used the OpenAI API but never built an agent loop
For: Working engineers committing to a career pivot into AI
For: Anyone whose primary LLM is Claude (or who builds with Anthropic API)
For: Data analysts and engineers already on DataCamp
For: Developers using Cursor casually who want to unlock advanced features
For: Working developers wanting to learn the 2026-grade AI coding workflow
Vendor-published and community-vetted resources — start with the one marked “primary”.
The canonical reference — setup, agent mode, MCP, hooks, sub-agents, all in one place.
Hands-on patterns for the Anthropic API + Claude Code. The patterns generalize to most LLM tooling.
Vendor-published deep-dives on the production features most users underuse.
Different surfaces, both excellent. Claude Code is terminal-native and shines in agentic workflows where the LLM drives multi-step pipelines (refactors, audits, migrations). Cursor is IDE-native and shines in the inner loop of code-editing (composer mode, inline edits). Most senior engineers in 2026 use both — Cursor for active editing, Claude Code for background agentic work.
Yes for sustained use — the rate limits on the free tier won't support real workflows. Pro ($20/mo) covers casual use; Max ($100-200/mo) is the right tier for engineers using Claude Code as their primary tool. The economics work out vs API tokens for >2 hours/day of use.
MCP servers tied to your specific tooling. A well-built MCP server for your codebase's database schema, internal API, or documentation transforms what Claude Code can do — from "thoughtful junior dev" to "actually knows your system." The investment is 2-6 hours per MCP server; the payoff is continuous.
Curated by editors who have built agents in production. Free + paid picks ordered by what we'd recommend to a friend.
The shortlist for learning to prompt LLMs in 2026 — separated by whether you're a developer or not.
The LangChain learning path — official short courses plus deeper paid alternatives.
Get 3-10x faster on Cursor, Claude Code, and the rest of the 2026 AI coding stack.
A no-bullshit AI curriculum for working software engineers. Free where possible, paid only where it pays back.
AI literacy for founders, sized for an 8-week sprint. No PhD required.
AI fluency for PMs — built around the decisions you'll actually make.
Ready to use Claude Code?
See Claude Code review & pricing →