The Best AI Coding Agents, Compared by How You Work

The best AI coding agent is the one that fits the way you already work, because the leading agents now do the same core job: read a codebase, edit files, run commands and tests, and keep going until the task is done. What separates them is structure. If you work in a terminal, look at Claude Code, Codex CLI, Gemini CLI, GitHub Copilot CLI or Aider. If you work in an editor, look at Cursor, Copilot agent mode in VS Code, or Windsurf, now Devin Desktop. If you want to hand off a task and get a pull request back, look at the cloud agents from GitHub Copilot, Codex, Cursor and Claude Code. This page gives the six questions that decide it, then a short, fair paragraph on each agent, with a link to a fuller comparison where one exists.

Six questions to ask before choosing

1. Where do you work? A terminal, an editor, a desktop app, or a browser tab you check later. Most agents now run in more than one place, but each has a home surface where it is most complete.
2. How much should it do without asking? Every agent here has a setting that runs from asking before each action to asking before none. Look at the steps in between, such as allowlists, classifiers that review risky calls, and sandboxes that limit what a command can reach.
3. How will you review its work? Diffs in the editor, checkpoints you can rewind, or pull requests reviewed on GitHub. Pick the agent whose review model matches how your team already reviews.
4. What does your team need? Configuration that lives in the repository, pull request review bots, admin controls, and billing that fits how your team pays. Plans change often; check each vendor’s current plans.
5. Which instruction file will it read? AGENTS.md is read by most agents here, but not all by default, and several have their own file too.
6. Does it speak MCP? MCP servers are how an agent reaches your tracker, docs and databases, and all the major agents here can use them. What is MCP, briefly: MCP in the glossary.

The agents, one by one

Claude Code

Anthropic’s agent. Per Anthropic’s overview↗ (opens in a new tab), it runs in the terminal, in VS Code and JetBrains, in a desktop app and on the web, all on one engine, so CLAUDE.md, settings and MCP servers carry across. It reads CLAUDE.md, and AGENTS.md when there is no CLAUDE.md. Approval is set by permission modes, from Manual to a classifier-reviewed auto mode, with checkpoints you rewind with /rewind. It also runs in CI, answers @claude on GitHub, and reviews pull requests. Suits people who start from a prompt and want the same agent in a terminal, a script and the cloud. Compared in Claude Code vs Cursor, Claude Code vs Codex and Claude Code vs GitHub Copilot.

OpenAI Codex

OpenAI’s agent runs as a CLI, an IDE extension for VS Code, Cursor and Windsurf, inside the ChatGPT desktop app, and as Codex cloud↗ (opens in a new tab), which runs tasks in isolated cloud environments and takes work from the web, GitHub, GitLab, Linear and Slack. It reads AGENTS.md. Locally it contains commands in an OS-enforced sandbox with network off by default and asks before leaving it. @codex review reviews a pull request. The CLI’s repository is open source under Apache-2.0. Suits AGENTS.md-first repositories and people who fire off several tasks and review them later. Setup is in Codex CLI setup, and the surfaces are compared in Codex app vs CLI vs IDE extension. Head to head: Cursor vs Codex and Codex vs GitHub Copilot.

GitHub Copilot

Copilot has three agent surfaces. Agent mode works in VS Code beside your code. The cloud agent works in a GitHub Actions environment and hands back a branch you review as a pull request. And Copilot CLI↗ (opens in a new tab) runs in the terminal on Linux, macOS and Windows, asking before risky tools with approve once, approve for the session, or reject. Copilot reads .github/copilot-instructions.md and AGENTS.md. Suits teams already on GitHub who want the agent, the pull request and code review in tools they use. The terminal route is in GitHub Copilot CLI. See the GitHub Copilot coding agent and GitHub Copilot agent vs Cursor agent.

Cursor

An AI code editor built around its agent, with Agent, Plan and Ask modes, run modes that decide what needs approval, and automatic checkpoints. Rules live in .cursor/rules, and it reads AGENTS.md and a root CLAUDE.md too. Cloud agents run in isolated virtual machines and start from the web, Slack, Linear or a pull request comment. Its command-line agent↗ (opens in a new tab) uses the same rules and MCP configuration as the editor. Suits people who want the agent and the diff inside the file they are reading. See Claude Code vs Cursor and Cursor rules for AI projects.

Gemini CLI

Google describes Gemini CLI↗ (opens in a new tab) as an open-source agent that brings Gemini into your terminal. It reads GEMINI.md files, and a setting lets it read AGENTS.md instead or as well. It has a read-only plan mode, reached with Shift+Tab or /plan, sandboxing, MCP servers, and a GitHub Action for pull request reviews and issue triage. Suits terminal users who want an open-source agent and sign in with a Gemini API key, Vertex AI or a Gemini Code Assist Standard or Enterprise licence; since 18 June 2026 it no longer accepts personal Google sign-in for the free tier or Google AI Pro and Ultra, as Gemini CLI vs Gemini Code Assist explains. See Gemini CLI plan mode, Gemini CLI vs Claude Code vs Codex CLI and connecting Gemini CLI to a board. Google’s newer agent-first tool is compared in Antigravity vs Claude Code.

Windsurf, now Devin Desktop

Windsurf has become Devin Desktop, and the Devin Desktop FAQ↗ (opens in a new tab) says existing features, extensions and workflows carry on. Its built-in agent is now Devin Local, with Normal, Plan and Ask modes and MCP servers; new conversations no longer start on the older Cascade agent. It reads rules from .devin/rules, still reads .windsurf/rules and .windsurfrules, and picks up AGENTS.md. It now opens on the Agent Command Center, a view of all your agents. Suits editor users who want an agent built into the IDE. Connecting it: Windsurf on fenbs.

Aider and the rest

Aider is an open-source pair programmer for the terminal with a distinctive review model: it commits every edit to git with a descriptive message, and /undo discards the last one. Conventions go in a file you load with --read. It suits people who want every change in git history as it happens. Beyond these, editors and IDEs increasingly host several agents at once; VS Code, for example, can run Claude and Codex sessions beside Copilot’s own, so the agent and the editor are no longer the same choice. More comparisons: Cline and Kilo Code vs Claude Code, Kiro vs Claude Code and OpenCode vs Claude Code.

Match the agent to the situation

• You live in a terminal and script your tools: Claude Code, Codex CLI, Gemini CLI, Copilot CLI or Aider. For scripts and CI, Claude Code has claude -p, Codex has codex exec, and Cursor’s command-line agent has a print mode too.
• You live in an editor and want to watch changes land: Cursor, Copilot agent mode in VS Code, or Devin Desktop.
• You want to hand off an issue and review a pull request: Copilot’s cloud agent on GitHub, Codex cloud, Cursor’s cloud agents, or Claude Code’s cloud sessions.
• Your code is not on GitHub: Cursor’s cloud agents clone from GitLab, Bitbucket and Azure DevOps, and Codex cloud connects to GitLab. Terminal agents work on any repository on your machine.
• You want open source: Gemini CLI, Aider and the Codex CLI repository are all published under open-source licences.
• You work alone: pick one agent, keep one backlog, and review every diff before you commit; the day-to-day is in a solo developer’s workflow with AI coding agents.
• Your team uses several: fine. Share one AGENTS.md, give each agent its own branch, and assign work from one place, as in orchestrating coding agents.

What stays the same whichever you pick

Three things outlast the choice of agent. An AGENTS.md with your build commands, conventions and no-go areas, which most of these agents read; AI context files compared shows which reads what. MCP servers, which the major agents here all use, so your tools are not tied to one vendor. And the list of work itself, which should not live in any one agent’s chat history.

That last one is where fenbs fits. Every agent on this page that speaks MCP can join a fenbs board at https://fenbs.ai/api/mcp. Each signs in through your account, you tick what it may do, and every change is recorded in History under the assistant’s name on your behalf. Tasks move through To Do, Next Up, In Progress and Completed, each with a problem, a plan and how it was tested, so switching agents next month does not mean losing track of what the last one did.