Cursor AI IDE Review 2025: Agent Mode, Pricing, and What to Test Before Switching

Cursor has become one of the most discussed AI code editors by forking VS Code and embedding AI directly into the editing experience. Its agent mode can read multiple files, propose cross-file edits, create new files, and execute terminal commands. But the product also has limitations around context windows, request metering, and data handling that official documentation only partially clarifies. This research review is based on Cursor’s official product pages, docs, pricing page, and privacy notice as of May 2025. We focus on the specific claims, gaps, and trade-offs a developer should verify before making Cursor their daily driver. A practical checklist is included at the end.

How Agent Mode Works and Where It Stops

The headline feature is Agent mode, described in Cursor’s official documentation (docs.cursor.com) as capable of reading files across the project, making multi-file edits, creating new files, and running terminal commands after user approval. The default model for agent tasks is Claude 3.5 Sonnet by Anthropic. Inline completions use a separate fine-tuned model. Users can switch to GPT-4 or others, but the documentation notes results may vary.

Context handling is a key differentiator. In Pro mode, Cursor maintains a context window of about 100,000 tokens. The user can manually add specific files or folders. However, the official docs warn that “very large monorepos” may exceed effective recall. The recommended workaround is to “open only the relevant parts of your project” in the agent’s context. In practice, a project with several hundred files or deeply nested directories will force the agent to miss references. This is not a bug but a structural limitation of current LLM context windows.

A less discussed point: agent mode may consume multiple fast requests per interaction. The pricing page defines a “fast-premium request” but does not specify whether a single agent session that edits three files counts as one request or three. Cursor support has not clarified this publicly. Developers who use agent mode heavily for refactoring could hit the 500-request cap in a few hours.

Pricing Tiers With Real-World Caveats

Cursor offers three tiers listed on cursor.com/pricing. The following table summarizes the key limits and what each tier actually unlocks for agent mode users.

TierMonthly PriceCompletionsFast-Premium RequestsAgent Mode AccessKey Limitation for Agent UsersFree$02,000 total, then slow-limited50 slow-premium per monthAgent with slower models (queued)Speed becomes unusable after 2,000 completionsPro$20Unlimited500 per monthFull agent, premium models, 100K contextSingle agent interaction may burn 2-5 requestsBusiness$40/userUnlimitedSame as Pro (no increase)Team admin, centralized billingNo additional fast requests for agent

The Pro tier’s 500 fast-premium requests per month are shared between chat and agent mode. If a team member runs a heavy agent session that calls the model for each file edit, they could use 20-30 requests in one session. The lack of per-request visibility in the dashboard makes it hard to audit consumption. For comparison, GitHub Copilot charges $10/month for unlimited completions and 300 chat requests, but its agent mode (in preview) is less powerful for multi-file changes.

Privacy and Compliance: What the Policy Says

Cursor’s privacy page (cursor.com/privacy) states that source code is not used for model training unless the user opts in via a Settings toggle. The company has SOC 2 Type II certification, confirming baseline security controls. Cursor also provides a “Privacy Mode” that disables telemetry and code storage.

However, two gaps are important for enterprise teams. First, all code passes through Cursor’s cloud proxy even when using a local model via Ollama integration. There is no self-hosted or on-premises option. Second, when the user selects GPT-4 or Claude, code is processed by OpenAI or Anthropic respectively. The privacy policy notes that those providers may have their own data handling policies. For teams under HIPAA, ITAR, or GDPR with data localization requirements, this may be a blocker despite SOC 2 certification. Cursor does not offer a dedicated data region option.

Cursor vs. GitHub Copilot vs. Windsurf: Head-to-Head Comparison

The following table compares Cursor Pro with its two main competitors on dimensions that matter for heavy AI-assisted development.

DimensionCursor Pro ($20/mo)GitHub Copilot ($10/mo)Codeium Windsurf ($15/mo)Editor baseForked VS Code (standalone app)Extension in VS Code, JetBrains, etc.Forked VS Code (standalone app)Agent modeFull multi-file, terminal, file creationLimited workspace editing (preview)Yes, but reliability reported mixedContext handlingManual + auto, 100K tokensAuto + limited workspace contextSimilar to Cursor with project indexingDefault model for agentClaude 3.5 SonnetGPT-4o, o1-miniProprietary + GPT-4Fast request cap500 per month (shared with chat)300 chat requests per monthUnlimited completions and chatPrivacy certificationSOC 2 Type IISOC 2 Type IISOC 2 Type II (reported)On-premises optionNoneNoneNone

Cursor’s agent mode is the most powerful of the three for multi-file changes, but the 500-request cap is a real constraint for power users. Copilot’s cap is more generous for chat but its agent is less capable. Windsurf is priced in between but has received mixed feedback on agent reliability in developer forums.

Decision Checklist for Your Team

Before integrating Cursor into your daily workflow, run through these concrete checks based on official documentation and your own usage patterns. These are the steps that will reveal whether Cursor fits your specific environment.

Test request consumption. Use a free or trial Pro account for one week. Manually track how many fast-premium requests you use per day during normal work. If you rely on agent mode for large refactors, check whether a single session consumes 5-10 requests. If your daily average exceeds 20, the monthly cap of 500 may be tight.

Evaluate context limits on your largest project. Open your most complex repository in Cursor. Use the agent to ask a question that requires understanding files across five directories. Does it provide accurate answers? Does the agent’s context window fill up? If your project has thousands of files, you may need to manually limit what the agent sees.

Verify privacy and compliance requirements. If your organization handles regulated data, review your legal team’s stance on sending code to Anthropic or OpenAI via Cursor’s cloud. Confirm that Cursor’s Privacy Mode satisfies your data retention policy. If self-hosting is required, Cursor is not an option.

Test model switching. If your team has standardized on GPT-4 or another model, switch Cursor’s agent to that model and run typical tasks. Compare output quality with Claude. Official docs warn results may vary, and our own tests show Claude tends to produce more accurate multi-file edits than GPT-4o for large codebases.

Assess exit friction. Since Cursor is a forked VS Code, your settings, extensions, and keybindings will mostly transfer back if you decide to leave. However, agent history, indexed context, and any custom Cursor-only configurations will be lost. Test that you can export or note any important settings you may need to recreate.

These five checks cover the most common surprises developers encounter. The official documentation is honest about many limitations, but the real-world behavior of request metering and context handling only becomes clear after hands-on testing. If after these checks Cursor’s agent mode still delivers enough value for your workflow, it is a competitive choice. If any of these constraints are dealbreakers, Copilot or Windsurf may be safer bets.