Cursor

Cursor is an AI-powered development environment and agent platform aimed at software engineers and engineering teams. From the documentation structure, it combines a local client (with configuration for languages, themes, keyboard shortcuts, and inline editing), an automation-focused CLI, and a cloud agent API you can embed into web and mobile applications. The core idea is to give you AI agents that can understand your codebase, take actions in your tools, and automate repetitive engineering tasks.

The product is tightly integrated with typical developer workflows. There are official docs for Git, GitHub, and GitLab integrations, plus an agent that can use a browser and a terminal, suggesting it can, for example, run commands, inspect logs, and pull in external information. A context system with semantic search, ignore rules, skills, and subagents helps the agent stay grounded in your repository. For larger organizations, there are team and enterprise features for identity and access management, SSO/SCIM, admin APIs, analytics, network configuration, and data governance.

Getting started appears to involve installing the Cursor client (via a downloads page), configuring language support (Python, JavaScript/TypeScript, Java, iOS/macOS/Swift, and more), and optionally setting up Git hosting integrations. You can also use the CLI in headless mode or via GitHub Actions, and integrate the cloud agent via HTTP endpoints and webhooks in your own web or mobile apps.

Based on the documentation sitemap, Cursor is more than a simple autocomplete tool — it’s positioned as an agentic system that can browse the web, execute terminal commands, and orchestrate multi-step workflows through “agent workflows,” subagents, and a Model Context Protocol (MCP) integration for external tools. There are dedicated cookbooks for large codebases, web development, data science, automated bug fixing (Bugbot), CI fixes, secret audits, translation of localization keys, and documentation updates, which indicates the tool is meant to operate autonomously over real projects rather than in isolated snippets.

However, some important details are not visible from the crawled content. The specific AI models used, how privacy is enforced at the model/provider level, and the exact pricing structure are not clear. While there is extensive enterprise documentation for compliance, monitoring, LLM safety controls, and data governance, you would need to review those pages directly to understand whether the setup meets strict regulatory or on-prem requirements. If you’re looking for a no-code business automation tool or a general-purpose personal assistant, this isn’t a fit — it’s clearly oriented toward developers comfortable with code, CLIs, and CI/CD integration. Pricing details are not apparent from the sitemap alone, so expect to check their pricing and billing pages or contact sales for specifics.