Cursor review

Cursor is a commercial AI coding agent from Anysphere, delivered through a desktop app, a terminal CLI, and workflows connected to Slack and GitHub. It sits alongside your code editor and repository rather than acting as a library or a self-hosted server. The product is designed to take coding tasks from planning through implementation, testing and a reviewable result.

The homepage describes agents using their own computers to build, test and demo features. Cloud agents can run in parallel on tasks for hours or days, while developers review completed work. Cursor also offers model selection across OpenAI, Anthropic, Gemini, SpaceXAI and its own Composer. In a codebase, that makes Cursor an agent orchestration layer that works against project files and can feed changes into existing review workflows. It is not a replacement for your source control, CI or human review: the advertised workflow ends with work for you to inspect.

Cursor's documented integration surface is its desktop app, terminal CLI, Slack integration and GitHub pull-request workflow. The CLI installs with curl https://cursor.com/install -fsS | bash. In Slack, users can tag the agent to open or review pull requests; in GitHub, the agent can review and open pull requests. The homepage also describes model selection across OpenAI, Anthropic, Gemini, SpaceXAI and Composer.

Cursor is presented as a coding application and agent, not as an API-first service. The homepage does not name a public API style, SDK, programming language or webhook interface. Before building an automated integration, confirm SDK and API support in Cursor's vendor documentation rather than assuming the CLI or Slack workflow exposes a stable developer API. The CLI is the named terminal integration; the homepage does not provide a language-specific package or sample integration contract. For a team adopting Cursor, start with its desktop or CLI workflow and verify the supported authentication, permissions and repository access in the docs.

Cursor's listed plans start with Free at $0 per month, which includes limited agent requests and limited Chat requests. Plus is $8 per month, Premium $30, Super $100 and Ultra $200. The plan descriptions say Plus is limited to Grok models; Premium includes four times Plus usage, Super 15 times and Ultra 50 times. Premium also lists cloud agents and automations, code hosting and AI code reviews. Third-party models are billed separately at API list price.

Teams starts at $30 per user per month, with usage varying by seat tier; it lists centralized billing, administration, SAML/OIDC SSO and team-wide privacy settings. Enterprise has custom pricing and lists pooled usage, invoice or PO billing, SCIM seat management, spend controls, audit logs and service accounts. The pricing page lists usage top-offs when an allowance is exhausted, but does not give their price here. Check expected model usage and top-off costs before setting a production budget. No annual discount is listed.

Cursor is sold as a commercial product, not presented as an open-source editor or agent server. The homepage describes a desktop app, CLI and hosted cloud agents; it does not describe a self-hosted deployment path. The vendor does not publish an open-source license, self-hosting option or data-export guarantee on the homepage, so teams with source-code residency or exit requirements should ask Anysphere about those terms before adoption.

Migration risk depends on how much of your workflow relies on Cursor-specific agent behavior, Slack handoffs and review automation. Your repository and normal Git history remain the practical boundary for code changes, but the homepage does not document an export format for agent context, tasks or configuration. Keep project instructions and important decisions in files your team controls, and make sure generated changes remain reviewable as ordinary repository changes. That reduces dependence on app-specific context if you later move to another editor or agent.

Cursor can help with production code, but the advertised agent workflow is not a substitute for CI, tests, security review or change controls. The homepage describes agents testing and demoing features, but does not publish reliability targets, rate limits or a production SLA. Before rolling it out, check repository permissions, privacy settings, model-routing behavior, usage controls and how agents access secrets or deployment tools. Teams and Enterprise list privacy and administration controls; confirm that their specifics meet your requirements.

Developers on Reddit report both time savings and problems with mismatched project patterns, unwanted changes and large diffs. One commenter says they review proposed changes one by one and work on branches; another says agent-generated code can leave them lost in the diffs. Those reports point to a practical safeguard: assign bounded tasks, ask for a plan on broad changes, inspect diffs and run the project's own tests. Parallel cloud agents may expand throughput, but they also create more work to review.