3 docs tagged with "agents"

Coding agents go beyond inline suggestions — they can read your codebase, run commands, browse documentation, and iterate through a task autonomously. This page explains how they work and how to use them effectively.

Model Context Protocol (MCP) is an open standard for connecting AI models to external data sources and tools. Instead of every AI tool reinventing integrations, MCP provides a single protocol that any client — Copilot, Cursor, Cline, Claude Code — can use to talk to any server: a database, the GitHub API, your file system, a browser.

A single AI agent has limits — context window size, task scope, and specialization. Multi-agent systems address these by having multiple agents collaborate, each with a defined role. This page covers the patterns and frameworks that make this practical.