Cursor AI Code Editor: Build Faster
Cursor is a coding agent for building and maintaining software. The official product page presents desktop, terminal and cloud workflows, while its documentation organizes the product around understanding code, planning changes and inspecting the resulting work. It suits developers who want AI assistance inside an existing development process.
Understand a repository and plan changes
Cursor supports codebase understanding, feature planning, bug fixes and change review. Its documentation describes tracing how a repository fits together, using Plan Mode to scope features, and inspecting diffs and running checks before merging.
You can customize Cursor with plugins, skills, MCPs and rules. Those options let a team supply context and connect tools around the coding task. The docs list integrations with services including GitHub, GitLab, Azure DevOps, Bitbucket, Slack and Linear. Check the setup for the service you use rather than assuming every integration shares the same access requirements.
Run agents in the cloud
Cloud agents run in isolated virtual machines with full development environments. The cloud-agent guide explains that agents can build, test and interact with changed software in those environments, including desktop and browser control. It also supports work across multiple repositories.
For repository-based work, an account administrator must connect source control. The environment needs the repositories, dependencies and access required for the task. Agents work on separate branches and push their changes for handoff, so reviewing the resulting code remains part of the development workflow.
Check plans and model usage
The pricing page distinguishes a free Hobby plan with limited agent requests from paid individual, team and enterprise options. Paid access does not mean unlimited model usage: plans include usage allowances, with on-demand usage available after those allowances are consumed.
The cloud-agent documentation separately describes model-based API pricing and a spend limit when you start using cloud agents. Before handing off a large task, check the selected model, environment and billing controls. A small bug fix with a reproducible check is a useful first evaluation of the workflow; this entry does not claim a measured productivity gain.