AstraCode vs Cursor vs GitHub Copilot

Three ways to put an AI agent on your code. One of them chooses the model for you, proves its own tests, and follows you from the editor to CI.

Statements about Cursor and GitHub Copilot come from their own pages, were checked on 1 October 2026, and are cited at the foot of this page.

Cursor is an AI-first editor. GitHub Copilot is an assistant that lives in the editor you already run and across GitHub. AstraCode is an AI-native coding environment: an editor built around its agents, the same agents in your terminal, CI and pull requests, and AstraOne choosing the model.

All three now plan, edit and run commands across a repository. What separates them is how much the agent proves before it reports, who chooses the model, and how far the agent reaches beyond the editor.

Side by side

	Cursor	GitHub Copilot	AstraCode
Agents that plan, edit and run commands across the repository	Yes	Yes, agent mode	Yes
MCP servers	Yes	Yes	Yes
Rules or custom instructions, skills and hooks	Yes	Yes	Yes
A CLI for the terminal and CI	Yes	Yes	Yes
Code review on pull requests	Yes	Yes	Yes
The agent is the editor, not an extension in it	Yes	No	Yes
Chooses the model, and escalates when a check fails	See their docs	See their docs	Yes, AstraOne
Runs your tests before it reports	See their docs	See their docs	Yes, every run
Proves its tests fail without the change	See their docs	See their docs	Yes
Refuses an infrastructure apply until a plan has run	See their docs	See their docs	Yes

Where a row reads "See their docs", we are not going to characterise somebody else's product for you. Their documentation is linked at the foot of this page.

Why teams choose AstraCode

For heavy AI-native development. Bigger autonomous tasks, with plan steps handed to agents of their own and parallel agents that never collide.
For work they can trust. The agent proves its own tests and says so when it cannot verify something.
For no model guesswork. AstraOne chooses, and escalates on a failed check.
For one agent everywhere. The editor, the terminal, CI, pull requests, and JetBrains IDEs and Zed.

AstraOne chooses the model

Most AI editors hand you a list of models and leave the choice to you: which one is good at this, which one will finish, which one to switch to when it stalls. AstraCode takes that job off you. AstraOne runs the model measured to finish real repository work, checks the result, and when a check fails it brings in a stronger model and keeps going.

Nothing to research. No model list to compare and no attempts spent finding out the hard way which one fits.
Escalation on evidence. A failed check, not a guess, is what brings in the stronger model.
Always visible. Every step names the model that served it.
Your key, your choice. Bring your own provider key and you can pick any model yourself.

It checks its own work

Every agent run follows the same loop:

Plans the change across the whole repository, not your open tabs.
Edits the files.
Runs your tests, the ones already in your project.
Proves the tests. It undoes its own change underneath them and confirms they fail without it. A test that still passes proves nothing, and sends the run back.
Reads the output and fixes what it broke.
Hands you the diff, hunk by hunk, with a checkpoint before every turn so any run can be undone completely.

If it cannot verify something, it says so instead of reporting success. Every run ends with what changed, what it checked after its last edit, and anything left for you to do.

Powerful coding agents for bigger, autonomous work

AstraCode is built for heavy AI-native development: bigger autonomous tasks that take many steps, many files and more than one attempt. Its agents plan, implement, test and review, and coordinate larger work across agents of their own.

Plan, then build. Plan mode agrees the approach before any code changes, and each step of the plan can be handed to an agent of its own.
Agents in parallel. Run several at once, each in its own git worktree, so they never collide.
Subagents. Self-contained parts of a large job go to subagents with their own context.
Goals, not prompts. /goal keeps working in rounds until the goal is met on evidence, and /loop re-runs a prompt on a schedule.
Automation. The CLI runs the same agent from a script or a CI job: one task in, a JSON result out, and an exit code your pipeline can act on.
Debug mode. It reproduces and measures a bug before it fixes it, then removes the logging it added.
Long-running work. Dev servers and builds run in the background while it keeps going, and it reads their output as it arrives.
A real browser. It opens your app, clicks through it, reads the console, and checks again after a fix.

Diff review and code review, built in

In the editor. Every change arrives as a diff you accept or reject hunk by hunk.
From the terminal. astracode-agent review reviews a branch and reports each finding with the input that triggers it and the wrong result that follows, as text or as JSON for a pipeline.
On every pull request. The AstraCode Review GitHub Action comments with the problems it can show will break, most serious first, and can fail the check above a severity you set.

Custom workflows, shaped to your team

Build your own workflows on the agent, and share them through the repository:

Rules that live in the repository, so the whole team gets the same agent.
Skills that teach the agent a procedure to follow the same way every time.
Hooks that run your own script before an action, and can approve, block or rewrite it.
MCP servers, local or over HTTP, so the agent can use your issue tracker, database and internal services. Servers your organisation approves arrive already configured.
Memories: one durable fact at a time, saved only when you agree.

Wherever your team works

The AstraCode editor on macOS and Linux. Your extensions, keybindings and settings come across on first launch.
Windows: AstraCode as an extension in the editor you already use, with the same account and the same agent.
The terminal and CI: the AstraCode CLI holds a conversation, runs one task from a script or a pipeline and exits, or reviews a branch.
JetBrains IDEs and Zed: the same agent, inside their agent panels, through the CLI.

Prove it in ten minutes

Take a repository you know, with a suite that passes:

Ask for a change touching three or four files.
Before reading the diff, break something it just wrote.
Ask it to continue.

An agent that runs and proves your tests notices. Run that on what you use today, then run it here.

Sources

Cursor — Cursor's own product pages, for what the editor is and what it does. Checked 1 October 2026.
Cursor documentation — Cursor's own documentation of its agent, MCP, rules, skills, hooks and CLI. Checked 1 October 2026.
GitHub Copilot documentation — GitHub's own description of Copilot, its agent mode, MCP support, CLI, code review, skills and hooks. Checked 1 October 2026.

Ten minutes, free, no card

Give it a change across a few files. Break something it wrote. Watch it notice, fix it, and prove the fix.

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