"Which AI coding agent should I use: Cursor, Claude Code or Codex?" comes up constantly, and the honest answer has changed. The leading tools have converged a lot. They read your repo, edit across files, run commands, support MCP and agent skills, and most of them read AGENTS.md. Choosing one is now less about raw ability and more about where the agent runs and how it fits the way you work.
This guide compares the main options using only what their official docs say. We've left out pricing and model lists on purpose: both change often, so check each vendor's pricing page on the day you decide.
The quick map
| Tool | Where it runs | Good fit if you… |
|---|---|---|
| Cursor | Its own editor, plus Cloud Agents (web, desktop, iOS, Slack, GitHub, Linear, API) and a CLI | want an AI-first editor and to hand off parallel tasks to the cloud |
| Claude Code | Terminal, VS Code and JetBrains, a desktop app, and the web | live in the terminal or want one agent across many surfaces |
| Codex | CLI, IDE extension, the ChatGPT desktop app, and Codex cloud | use ChatGPT already and want local + cloud in one workflow |
| GitHub Copilot | IDEs, the Copilot CLI, and a cloud agent on GitHub.com | want work to start and end in GitHub issues and pull requests |
Cursor
Cursor describes itself as "a coding agent for building ambitious software", built around its own editor (Cursor docs). Two things stand out:
- Cloud Agents. These run in isolated cloud VMs with full development environments, and you can run "as many agents as you want in parallel" without your machine being online. You can start them from the desktop app, cursor.com/agents, the iOS app, Slack, GitHub or Bitbucket comments, Linear, or the API. They produce pull requests along with screenshots, videos and logs showing how the agent checked its work. Cloud Agents are billed at API pricing for the model you pick, and you'll be asked to set a spend limit (Cloud Agents docs).
- Model choice. Cursor's docs list models from several providers (Anthropic, OpenAI, Google, its own Composer models and others), so you can switch models without switching tools (Cursor docs).
Cursor also has a CLI (agent) that shares its MCP configuration with the editor (Supabase MCP docs). It loads agent skills from .agents/skills/ and .cursor/skills/, and also from Claude's and Codex's skill folders (Cursor skills docs).
Claude Code
Anthropic's Claude Code is an "agentic coding tool that reads your codebase, edits files, runs commands, and integrates with your development tools". It runs in the terminal, in VS Code and JetBrains, in a desktop app and on the web. According to the docs, "each surface connects to the same underlying Claude Code engine", so your CLAUDE.md, settings and MCP servers work across all of them.
What it's strong at, per the docs:
- Scripting and automation. It follows the Unix philosophy: you can pipe logs into it, run it in CI with
claude -p, or chain it with other tools. - Routines and parallel work. It supports cloud and desktop scheduled tasks, subagents, and an Agent SDK for building your own agents.
- Moving between surfaces. You can start a task on the web or your phone and pull it into your terminal, or continue a terminal session in the desktop app.
- Shared rules. If your repo already has an
AGENTS.md, Claude Code "can read that in place of aCLAUDE.md."
Most surfaces require a Claude subscription or an Anthropic Console account. The terminal CLI, VS Code and JetBrains also support third-party providers (overview).
Codex
OpenAI's Codex CLI works on your local repo from the terminal. It has a /review command for checking changes before you commit, codex exec for scripts and CI, codex cloud to send work to a cloud environment, and codex mcp to connect tools. /init creates an AGENTS.md for the project. Skills are available in the ChatGPT desktop app, the Codex CLI and the IDE extension, and skills packaged as plugins also work in ChatGPT on the web and mobile (Codex skills docs).
You sign in with your ChatGPT account or another available method on first run. That makes Codex the natural choice if your team already works inside ChatGPT (Codex CLI).
GitHub Copilot
Copilot's cloud agent on GitHub.com can research a repo, plan changes and implement them in an ephemeral cloud environment. It handles branches, commits and pull requests for you. GitHub documents some clear limits that are worth knowing before you plan around it:
- It works on one repository per task, one branch at a time, and opens one pull request per task.
- Each session has a maximum run time of 59 minutes.
- It only works with repositories hosted on GitHub.
If your whole process already lives in GitHub issues and PR reviews, those limits may not matter, and the integration is hard to beat.
And the others
The AGENTS.md site lists more than 20 tools that read the format, including Gemini CLI, Jules, Windsurf, Devin, Zed, Aider, opencode, Warp, Junie and goose. Many of these are good choices too, especially if you want open-source tools or a particular editor.
How to choose an AI coding agent: five questions
- Where do you spend your day? In an editor, choose an editor-first tool (Cursor, or Copilot/Claude Code/Codex inside VS Code or JetBrains). In a terminal, Claude Code and the Codex CLI feel natural.
- Do you want to delegate work in parallel? All four offer some form of cloud or background agent. Compare how each one sets up the environment (dependencies, secrets, network access), because that decides whether the agent can actually test its work.
- Where does your work start and end? If it's GitHub issues and PRs, Copilot's cloud agent fits. Cursor's Cloud Agents can be started from Slack, Linear and GitHub, and Claude Code can turn a Slack mention into a pull request.
- How much does model choice matter to you? Cursor's model menu covers several providers. Claude Code and Codex are built around their own companies' models.
- What does it cost at your usage? Run a real task from your own backlog in each tool you're considering, then check the bill or usage dashboard. Benchmarks won't tell you this.
Don't marry a tool: keep your setup portable
The good news is that switching is cheaper than it used to be, because the setup that matters now uses shared standards:
AGENTS.mdfor project rules (how to write one). Codex, Cursor, Copilot's coding agent and many others read it, and Claude Code can use it in place ofCLAUDE.md.- Agent skills (
SKILL.mdfolders) for repeatable procedures (how to write your first skill). They're supported by Claude Code, Cursor and Codex, and Cursor even loads the other tools' skill folders. - MCP servers for tools and data (how to add one to each tool). All four tools support MCP.
If you put your effort into these three instead of tool-specific features, you can try a new agent in an afternoon. Many teams end up using two: one in the editor for interactive work, and one in the cloud for background tasks.
Keep reading
- How to run coding agents safely: permissions, sandboxes and secrets
- AGENTS.md starter template for Next.js and Supabase
- 10 copy-paste AI coding prompts to ship a web app
FAQ
Which is the best AI coding agent?
There is no single best AI coding agent. Pick the one that runs where you work: Cursor for an AI-first editor, Claude Code or Codex for the terminal, and Copilot if your work lives in GitHub.
Can I use more than one coding agent on the same repo?
Yes. Most of them read AGENTS.md, support agent skills and connect to MCP servers, so one repository setup can serve several tools.
Does Claude Code read AGENTS.md?
Yes. Recent Claude Code versions read AGENTS.md when the project has no CLAUDE.md, and you can also import it from CLAUDE.md with an @AGENTS.md line.
How do I compare the cost of coding agents?
Run a real task from your own backlog in each tool you are considering and check its usage dashboard. Pricing changes often, so check each vendor pricing page on the day you decide.
