Cursor is an AI coding platform helping developers and engineering teams build software with AI. Cursor's product is designed for complex codebases, supports frontier models from leading providers, and gives teams tools to configure model access, MCP controls, and system-level agent rules. Cursor has over 50,000 businesses on its platform, including 67 percent of the Fortune 500. Over 150M lines of enterprise code are written per day with Cursor.
Agent: A human-AI programmer designed to multiply your effectiveness. Agent can take on complex coding tasks, run terminal commands, and edit code so you can focus on higher-level direction and architecture. From quick, scoped changes to large workflows, Agent handles the boilerplate and can even parallelize ideas by running asynchronous tasks in remote environments.
Tab: A specialized model for autocompletion that gets smarter the more you use it. Tab helps you stay in flow by offering accurate
For any custom pricing or private offers, please reach us at Contact Sales.
Highlights
Direct AI agents to build software Cursor is a dev environment where AI agents plan, write, and ship code. Run as many in parallel as you need and take their work all the way to a merged PR.
Local and cloud agents, one workflow Iterate with agents locally, or hand whole projects to agents running on their own in the cloud. Moving work between the two is seamless.
AI code review with Bugbot Bugbot reviews every pull request, catching logic bugs and security issues, then proposes one-click fixes. With agents that write code and review built into the IDE, Cursor covers the full lifecycle from writing to shipping.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
This contract prices two ways. The Licensed Seat dimension charges a set fee per seat per year, and you commit to a minimum of 1,000 seats. Each seat comes with an included amount of model usage that resets each billing cycle. The additional_usage dimension covers on-demand model usage beyond that included amount. It bills based on what you consume, billed in arrears. So your yearly cost combines the fixed per-seat commitment plus any variable usage. Administrators can set usage limits at the team and individual level to control the on-demand spend.
Top-of-mind questions for buyers
What does one Licensed Seat include, and how much usage comes with it?
A seat is a per-person license. Each seat includes a set amount of model usage that resets each billing cycle. You commit to a minimum of 1,000 seats. Administrators manage seats through a dashboard and can set usage limits at the team and individual level.
What happens if my team uses more model usage than the seats include?
Once you consume the usage included with your seats, on-demand usage continues under the additional_usage dimension. It bills based on what you consume, charged in arrears. Administrators can set usage limits per team and per person to keep this on-demand spend under control.
How do the Licensed Seat and additional_usage charges combine on my bill?
Your cost combines a fixed part and a variable part. The Licensed Seat charge is a set fee per seat per year, so it is predictable. The additional_usage charge only applies when consumption exceeds the included amount. Seat commitment usually forms the base, while on-demand usage varies with activity.
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AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Costory is the context layer between your cloud bills and your AI agents. Ask Claude or Cursor why your AWS bill spiked and get an answer grounded in your actual spend, team structure, deploys, and incidents. Queryable via MCP. No FinOps team required.
Your developers keep Cursor. Your prompts, code context, and AI spend stays in your AWS account. We set it all up, move your rules and skills across, and guide your team through the adoption.
CodeRabbit is the leading AI code review platform that delivers context aware feedback on pull requests. CodeRabbit uses AI to find and fix bugs or errors that can be missed during manual code reviews. It provides a clearer understanding of complex code changes, makes code refactor suggestions to enhance code quality, and helps you release features faster.
This product has charges associated with it for deployment, configuration, and ongoing support. Self-hosted OpenAI-compatible API gateway for Claude Sonnet 4, Opus 4.5, Haiku 4.5. Connect Cursor, Windsurf, Continue, or any OpenAI-compatible tool. No per-token costs, powered by Kiro subscription. Pre-configured, launch in 5 minutes.
AI-Native Coding in Cursor That Fits Right Into the VS Code Workflow
Reviewed on Aug 01, 2026
Review provided by G2
What do you like best about the product?
The AI integration in Cursor feels genuinely woven into the coding workflow instead of bolted on as an afterthought. Inline code generation and chat-based editing pull context from the whole codebase, not just the open file, so suggestions actually match existing architecture and coding patterns rather than generic boilerplate. Tab-to-accept autocomplete is fast and often predicts multi-line edits correctly, saving a lot of repetitive typing during daily development. The interface stays close to a familiar VS Code layout, so there's almost no learning curve coming from that ecosystem — getting started took minutes rather than a real onboarding process. Extensions and settings carry over smoothly, and the editor stays responsive even in larger projects with many open files. Integration with existing Git workflows and terminal usage feels seamless, and referencing specific files or symbols directly in a prompt makes debugging and refactoring noticeably quicker than switching to a separate AI tool. On pricing, the value holds up well against the time it saves — faster iteration and fewer context switches easily justify the subscription cost for a small technical team. Support has been reliable when needed, with documentation that covers most common issues, so there's rarely a wait to keep moving. Overall it's become a core part of the day-to-day coding process.
What do you dislike about the product?
Pricing gets frustrating once usage scales — the fast request limits on the standard plan get consumed quickly on larger codebases, and hitting that ceiling mid-task means either slowing down to conserve requests or upgrading to a higher tier sooner than expected. More transparency around real-time usage consumption would help, since right now it's often only clear after the fact. Performance can also dip on very large repositories — indexing takes noticeably longer, and the context window occasionally doesn't fully capture relevant files scattered across a big project, so suggestions miss dependencies living outside the immediate working directory. That means double-checking generated code more carefully on bigger builds than on smaller ones. The AI still occasionally hallucinates function signatures or library APIs that don't actually exist, especially with less common packages or internal libraries it hasn't seen much of, so verification against actual documentation remains necessary rather than optional. Multi-file refactors sometimes need manual cleanup afterward since the model doesn't always catch every downstream reference that needs updating. Onboarding new team members to the AI-specific features (custom rules, context management, model selection) takes more explanation than just picking up a standard editor, since getting real value out of it requires understanding how to prompt and scope context effectively. Minor learning curve, but it's there.
What problems is the product solving and how is that benefiting you?
Cursor is solving the friction of context-switching between writing code and getting AI assistance — instead of copying code into a separate chat window and pasting suggestions back, everything happens inline within the actual editor. This has meaningfully sped up day-to-day development, especially for repetitive tasks like writing boilerplate, generating test cases, and drafting initial implementations of well-understood patterns. It's also cut down significantly on time spent debugging, since the AI can scan across multiple files to spot the source of an error rather than manually tracing through the codebase file by file. For a small technical team without dedicated resources for every specialization, this has been a real force multiplier — junior or less experienced developers can move faster on unfamiliar parts of the stack because the AI helps bridge knowledge gaps in real time, whether that's an unfamiliar library, a new framework pattern, or legacy code someone else wrote. Refactoring large codebases has become considerably less tedious too. What used to mean manually updating dozens of related files can now be scoped and handled in a single pass with AI assistance, with far fewer missed references than doing it by hand. On the documentation side, having AI help generate and maintain inline comments and docstrings has improved code readability across the team, which matters a lot given multiple people touch the same codebase over time. The net benefit has been faster iteration cycles overall — less time spent on mechanical, repetitive work means more time available for actual architecture decisions, business logic, and problem-solving that requires real judgment.
Anilkumar C.
Great for Code Generation and Debugging, but Pricey and Token-Hungry at Times
Reviewed on Aug 01, 2026
Review provided by G2
What do you like best about the product?
Code generation, debug issues and ask questions about your project
What do you dislike about the product?
a bit expensive and some times it took more token then required
What problems is the product solving and how is that benefiting you?
It wrote a complete code of live activity in my swiftui project with actions and response
Hitarth Anand R.
AI that actually fits into the development workflow
Reviewed on Jul 30, 2026
Review provided by G2
What do you like best about the product?
What I like most about Cursor is that it feels like an IDE first and an AI tool second, which means I'm the guy in the chair. The AI is deeply integrated into the development workflow instead of feeling like a separate chatbot. Features like editing across multiple files, understanding the codebase context and making targeted changes save a lot time compared to constantly copying code back and forth.
I also appreciate that cursor doesn't try to replace the developer. It speeds up repetitive work, helps me navigate unfamiliar code, and lets me stay focused on solving the actual problem. It strikes a good balance between automation and keeping me in control, which makes it something i can use throughhout the day rather than occasionally
What do you dislike about the product?
Sometimes the AI makes broad changes when i want a small, targeted edit. It can also lose context in very large or complex codebases.
Occasionally, the suggested code looks correct but misses subtle project specific details. I would also like more transparency into why it chooses edits or approaches
What problems is the product solving and how is that benefiting you?
Cursor reduces the time spent on repetitive coding tasks like refactoring, debugging and boilerplate generation.
It understands the project context, so I spend less time explaining my code.
This lets me stay focused on solving problems instead of switching between tools.
As a result, I'm able to build features faster and maintain better development flow.
Antonio T.
A brutal productivity boost, although it consumes quite a lot of resources
Reviewed on Jul 29, 2026
Review provided by G2
What do you like best about the product?
That the AI is embedded in the core of the editor and not attached with a side widget. The autocomplete with Tab is super fast and being able to launch refactorings that affect multiple files at once from Composer saves you a lot of time. Being a fork of VS Code, the learning curve is zero; you open your workspace, it indexes the project, and you're working from the first minute.
What do you dislike about the product?
RAM consumption gets spammed quite a bit when indexing large repositories, and sometimes the credit system falls short if you push Composer hard daily. It would also be cool if the context management allowed for a bit more manual fine-tuning of the files to ignore.
What problems is the product solving and how is that benefiting you?
It takes the heavy carpentry off my shoulders: writing repetitive code, assembling types, and searching for documentation. By indexing the entire project, I can request refactorings that touch multiple files at once without having to manually copy and paste context. In the end, it translates into developing much faster and focusing on logic and architecture instead of wasting time on mechanical tasks.
Regarding integrations, being a direct fork of VS Code, you can import all your extensions, themes, and previous configuration with a click, and it connects very well with GitHub/GitLab repositories and external documentation through the option to add custom docs. In terms of ROI, the impact is immediate: with the monthly subscription, you recover those work hours in the first few days of use just with the time you save from writing repetitive code and migrating files.
In terms of support and onboarding, the curve is flat. The onboarding literally takes two minutes because it brings all your VS Code configuration at once, without having to relearn shortcuts or reinstall tools. On the support side, the community in its forum is super active and they release updates almost every week, fixing bugs and incorporating the latest models as they come out, so you never get stuck with an obsolete version.
A a.
Promising Features, Hampered by Severe Rate Limits
Reviewed on Jul 27, 2026
Review provided by G2
What do you like best about the product?
I use Cursor for coding HTML apps and Android/iOS apps, including Whisper translation apps. I like that it's really clean and pro. It offers a large range of models. I like the model composer because it's fast. The initial setup was easy and fast.
What do you dislike about the product?
I don't like that you hit your monthly limits in an hour. The rate limits are a big issue, and I think increasing them would really help. Also, even though Cursor is popular, I felt that Antigravity was better.
What problems is the product solving and how is that benefiting you?
I use Cursor for coding HTML and mobile apps. It offers a large range of models.