Learn · Coding agents
As of July 2026, entry pricing clusters around $10 to $20 a month. GitHub Copilot starts free for light use, with a Pro plan near $10 a month. Cursor and Claude Code both have plans starting around $20 a month, with heavier tiers running up to about $200 a month for high-volume professional use.
The cheaper plans cap how much you can use the most powerful models each month. Serious daily users often need a higher tier, and some tools have moved to usage-based billing where you pay for what you consume beyond an included allowance.
For a working developer, even the higher tiers are small next to the time they save. The real question isn't the subscription price. It's whether the tool fits how your team builds and reviews code.
Updated July 2026
Go deeper
Related
As of July 2026, the three lead the market with different shapes. Claude Code is a terminal-native agent built for deep, multi-file work. Cursor is a full AI-first code editor (a fork of VS Code) that blends editing and agent modes. GitHub Copilot is an extension that adds AI to editors you already use, with the broadest reach.
If you're not a developer and want to build something, a full AI editor like Cursor or a browser-based AI builder is usually the friendlier start, because it shows the app taking shape visually and handles setup for you. Terminal-based agents like Claude Code are more powerful but assume more comfort with a command line.
A coding agent is an AI tool that can write, edit, run, and debug code across a whole project, not just suggest the next line. You give it a task in plain language, and it reads the relevant files, makes changes across several of them, runs tests, and fixes what breaks, working in a loop until the job is done.
A code assistant suggests completions and answers questions while you drive: it finishes lines, explains errors, and drafts snippets on request. A coding agent takes a goal and executes the multi-file, multi-step work itself, running commands and tests. The assistant helps you type. The agent does the task.
A coding agent wraps an AI model in a loop with access to tools: reading and writing files, running terminal commands, and running tests. It reads your request, inspects the relevant code, makes an edit, runs the code to see what happens, reads the result, and repeats until the task passes or it gets stuck.
MCP (Model Context Protocol) is an open standard for connecting AI agents to external tools and data sources, like your database, a design tool, a ticketing system, or a file store. Instead of custom code for every integration, a tool exposes an MCP server and any MCP-aware agent can use it. It became a common standard across AI tools through 2025 and 2026.