How to Use Cursor: The AI-First Code Editor That Understands Your Entire Codebase

If you've ever wished your code editor could understand not just the file you're working on, but your entire project—its patterns, dependencies, and architecture—Cursor is that editor. It's built on VS Code, so everything you know transfers over, but with AI capabilities deeply integrated into every part of the development experience.

Unlike tools that bolt AI onto an existing editor as an afterthought, Cursor was designed from the ground up to make AI a native part of coding. It can predict your next edit across multiple lines, answer questions about your codebase, and even implement entire features while you provide high-level direction.

This guide will show you how to install Cursor, configure it for your workflow, and use its most powerful features effectively. We'll also cover how it integrates with DeployHQ for automated deployments once your code is ready.

Why Cursor Matters for Web Developers

Traditional code editors treat each file in isolation. When you ask an AI assistant for help, it only sees what you've pasted into the chat. This limits how useful its suggestions can be, especially for tasks that span multiple files or require understanding of your project's conventions.

Cursor changes this by indexing your entire codebase and building embeddings that let the AI understand relationships between files, existing patterns, and project structure. When you ask it to add a feature, it knows where similar features are implemented, what naming conventions you use, and which files need to change.

For web developers specifically, this means you can work at a higher level of abstraction. Instead of manually coordinating changes across controllers, views, routes, and tests, you describe what you want and let Cursor figure out how to implement it consistently with your existing code.

Step 1: System Requirements

Cursor runs on all major operating systems:

Operating Systems:

  • macOS 10.15 or higher
  • Windows 10 or higher
  • Linux (Ubuntu 20.04+, Debian 10+, or AppImage for other distributions)

Hardware:

  • Minimum 4GB RAM (8GB recommended)
  • SSD recommended for faster codebase indexing

Recommended:

  • VS Code experience (helpful but not required)
  • Git installed for version control integration

Step 2: Install Cursor

Installation is straightforward across all platforms.

Download and Install

  1. Visit cursor.com and download the installer for your operating system
  2. Run the installer and follow the prompts
  3. Launch Cursor

Linux users: The download comes as an AppImage file. Make it executable before running:

chmod +x cursor-*.AppImage
./cursor-*.AppImage

Import VS Code Settings

On first launch, Cursor will offer to import your settings from VS Code. This includes:

  • Extensions
  • Themes
  • Keybindings
  • User settings

Accept this option if you're coming from VS Code—it makes the transition seamless. Your entire development environment transfers over without manual configuration.

Initial Setup

During setup, you'll be asked about:

Keyboard shortcuts: Choose VS Code (recommended unless you're familiar with another editor like Vim or Emacs)

AI features: Enable the features you want to use. You can adjust these later in settings.

Step 3: Choose Your Plan

Cursor offers several pricing tiers:

Free (Hobby):

  • Limited completions and chat messages
  • Good for trying out the product

Pro ($20/month):

  • 500 fast premium requests per month
  • Unlimited slow requests
  • Access to GPT-4, Claude Sonnet, and other models
  • Most popular for individual developers

Ultra ($200/month):

  • Unlimited fast premium requests
  • Best for heavy users who hit Pro limits

Business ($40/user/month):

  • Team management features
  • Centralized billing
  • Admin controls

For most web developers, the Pro plan provides excellent value. If you find yourself regularly hitting the 500 fast request limit, consider Ultra.

Sign In

Click the account icon in the sidebar and sign in with your email, Google, or GitHub account. Your subscription is tied to your account, not your machine.

Step 4: Configure Cursor for Your Workflow

Before diving into features, let's configure Cursor for optimal use.

Select Your AI Models

Cursor supports multiple frontier models. Go to Settings > Models to choose:

For general use:

  • Claude Sonnet 4.5 — Best balance of speed and quality
  • GPT-4o — Strong alternative

For complex tasks:

  • Claude Opus 4.1 — Maximum capability for architectural decisions
  • Gemini 2.5 Pro — Good for large context windows

You can switch models on the fly depending on the task complexity.

Set Up Project Rules

Create a .cursorrules file in your project root to guide the AI's behavior:

You are helping with a Ruby on Rails application.

Follow these conventions:

- Use service objects for business logic, not fat controllers
- Prefer Stimulus over custom JavaScript
- Write RSpec tests for all new code
- Use Tailwind CSS for styling
- Keep methods under 10 lines when possible

When generating code:

- Follow existing patterns in this codebase
- Include proper error handling
- Add comments only for complex logic

These rules persist across sessions and ensure the AI follows your team's conventions.

Enable MCP Servers

Cursor supports the Model Context Protocol (MCP) to connect with external tools and data sources. Go to Settings > MCP to add servers.

Example: Adding Context7 for up-to-date library documentation:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

You can also create a .cursor/mcp.json file in your project for project-specific MCP servers.

Index Your Codebase

Cursor automatically indexes your project when you open it. For large codebases, this may take a few minutes initially. You can check indexing status in the bottom status bar.

To add external documentation, go to Settings > Indexing & Docs > Docs and add URLs. For example, adding your framework's documentation lets the AI reference it when answering questions.

Step 5: Core Features

Let's walk through Cursor's main features and how to use them effectively.

Tab Autocomplete

Cursor's Tab model predicts your next edit—not just the current line, but potentially multiple lines and even cursor position. It's trained on patterns in your codebase and understands context.

How to use it:

  • Type normally and watch for ghost text suggestions
  • Press Tab to accept the suggestion
  • Press Escape to dismiss

What makes it different:

  • Predicts multi-line edits based on recent changes
  • Suggests cursor position after accepting
  • Learns from patterns in your project

Cursor reports 28% higher acceptance rates with 21% fewer suggestions compared to traditional autocomplete—it suggests less, but with much better accuracy.

Chat (Cmd/Ctrl + L)

The chat panel lets you have conversations with the AI about your code. Unlike external chatbots, Cursor's chat understands your entire project.

How to use it:

  • Press Cmd+L (Mac) or Ctrl+L (Windows/Linux) to open chat
  • Ask questions or request changes
  • Use @ mentions to reference specific files, functions, or docs

Example prompts:

What does the OrderProcessor class do?

@app/services/order_processor.rb Explain the payment flow in this file

Why is this test failing? @spec/models/user_spec.rb:45

How should I implement rate limiting for our API endpoints?

Tips:

  • Reference specific files with @ to provide focused context
  • Ask follow-up questions to refine the response
  • Use "think step by step" for complex problems

Inline Edit (Cmd/Ctrl + K)

For quick, targeted changes, use inline edit. This lets you describe a change and see it applied directly in your code.

How to use it:

  1. Select code (or place cursor where you want changes)
  2. Press Cmd+K (Mac) or Ctrl+K (Windows/Linux)
  3. Describe what you want
  4. Review the diff and accept or reject

Example uses:

Add error handling for network failures

Convert this to async/await

Add validation for email format

Refactor to extract this into a method

This is faster than chat for small, focused edits.

Composer (Cmd/Ctrl + I)

Composer is for larger changes that span multiple files. It's like having a pair programmer who can implement features while you provide direction.

How to use it:

  1. Press Cmd+I (Mac) or Ctrl+I (Windows/Linux)
  2. Describe what you want to build or change
  3. Composer will identify affected files and make coordinated changes
  4. Review the diffs and accept or modify

Example prompts:

Add a user profile page that shows order history. Include the route, controller action, view, and update the navigation.

Refactor the authentication system to use JWT tokens instead of session cookies.

Add pagination to all index actions using Kaminari.

Composer understands your project structure and makes changes that follow your existing patterns.

Agent Mode

Agent mode takes Composer further by allowing the AI to work more autonomously. It can run commands, check results, and iterate on its own work.

When to use it:

  • Complex features that require multiple steps
  • Tasks that need verification (running tests, checking output)
  • Exploratory work where the AI needs to investigate first

How to enable:

Toggle "Agent" in the Composer panel, or use prompts that imply autonomous work like "implement and test" or "build and verify."

Example:

Implement a webhook endpoint for Stripe payment events. Write the controller, add signature verification, update order status based on the event type, and write integration tests. Run the tests to make sure everything works.

Agent will implement the code, run the tests, and fix any failures it finds.

Step 6: Advanced Features

Codebase Search with AI

Instead of grep or manual searching, ask Cursor questions about your codebase:

Where do we handle user authentication?

What files would be affected if I change the User model's email validation?

Show me all the places we make external API calls.

Cursor searches semantically, not just by text matching, so it finds relevant code even if the exact terms don't appear.

Fix with AI

When you see an error (lint warning, type error, test failure), Cursor offers a "Fix with AI" button. Click it to have the AI propose a fix based on the error message and surrounding context.

This is particularly useful for: - TypeScript type errors - Lint violations - Failing tests with clear error messages

Terminal Integration

Run commands and have Cursor help interpret the output. If a command fails, you can ask Cursor to explain the error or suggest fixes.

You can also describe what you want to do in natural language:

Run the tests for the User model

Deploy to staging

Show me recent git commits that touched the payment code

Bugbot (Add-on)

Bugbot is a separate add-on ($40/month) that integrates with GitHub to automatically review code changes—from both humans and AI—and flag potential issues. It watches for bugs, regressions, and inconsistencies that might slip through manual review.

Step 7: Best Practices for Effective Use

These patterns will help you get the most out of Cursor.

Use .cursorrules Effectively

Your .cursorrules file is one of the most powerful customization tools. Include:

  • Project-specific conventions
  • Technology stack details
  • Preferred libraries and patterns
  • Things to avoid

The more specific you are, the better the AI's suggestions will match your expectations.

Provide Context with @ Mentions

Don't make the AI guess which files are relevant. Mention them explicitly:

Add a similar validation to @app/models/order.rb as we have in @app/models/user.rb

This focuses the AI's attention and improves accuracy.

Review Changes Carefully

AI-generated code is usually good, but not always perfect. Always review diffs before accepting:

  • Check that the logic makes sense
  • Verify edge cases are handled
  • Ensure tests cover the new code
  • Look for unintended changes to other parts of the file

Use Agent Mode for Complex Tasks

For multi-step implementations, let Agent mode work iteratively:

  1. Describe the high-level goal
  2. Let the agent implement and test
  3. Review results and provide feedback
  4. Iterate until satisfied

This is more efficient than manually orchestrating each step.

Leverage Multiple Models

Different models have different strengths:

  • Use faster models (Sonnet) for routine tasks
  • Switch to stronger models (Opus) for complex architecture decisions
  • Use models with large context windows for understanding big files

Step 8: Team Features

If you're working with a team, Cursor offers features to keep everyone aligned.

Shared Rules

Check your .cursorrules file into version control so everyone on the team uses the same AI conventions.

Project-Level MCP

Use .cursor/mcp.json in your project (checked into git) to provide team-wide access to MCP servers without individual configuration.

Centralized Billing

The Business plan provides centralized billing and admin controls, making it easier to manage subscriptions across a team.

Step 9: Deploy with DeployHQ

Once Cursor helps you build features, you need to get them into production. DeployHQ automates the deployment process from your Git repository to your servers.

The Workflow

The combination of Cursor and DeployHQ creates an efficient development pipeline:

  1. Build features using Cursor's Composer or Agent mode
  2. Test locally with Cursor's terminal integration
  3. Commit changes using Cursor's Git integration
  4. Push to your repository
  5. DeployHQ deploys automatically to your staging or production server

Setting Up Automated Deployments

  1. Create a DeployHQ project and connect it to your GitHub, GitLab, or Bitbucket repository

  2. Configure your server with connection details (SFTP, SSH, or other protocols)

  3. Set up build commands if your project requires compilation:

    • npm run build for JavaScript projects
    • bundle install for Ruby projects
    • Any other setup your application needs

  4. Enable automatic deployments for specific branches (e.g., deploy main to production, staging to staging server)

Example Workflow in Practice

# In Cursor, use Composer to add a feature
> Add email notifications when an order ships. Include the mailer, 
> background job, and trigger it when order status changes to shipped.

# Cursor implements across multiple files

# Review the changes in the diff view
# Accept the changes

# Commit using Cursor's Git integration
> Commit these changes with message "Add shipping notification emails"

# Push to your repository
git push origin main

# DeployHQ automatically:
# - Detects the new commit
# - Runs build commands
# - Transfers files to your server
# - Runs any deployment hooks

The entire flow from describing a feature to having it live can happen in minutes.

Step 10: Troubleshooting

Common Issues

Slow indexing:

Large projects take time to index initially. Check the status bar for progress. You can exclude large directories (like node_modules or vendor) in settings to speed this up.

AI responses are generic:

Make sure you're using @ mentions to provide relevant context. Create a .cursorrules file with project-specific instructions.

MCP servers not working:

Check the MCP settings page for error messages. Verify the server command runs correctly in your terminal. Use the --mcp-debug flag if available.

Hit rate limits:

The Pro plan includes 500 fast requests per month. If you regularly hit this limit, consider the Ultra plan or adjust your usage to combine multiple small requests into larger ones.

Getting Help

  • Check Cursor's documentation at docs.cursor.com
  • Join the Cursor community forum
  • Use the feedback option in the app to report issues

Conclusion

Cursor represents a significant shift in how developers interact with their code editors. By understanding your entire codebase, it can provide suggestions and implement features that are consistent with your existing patterns—something that was impossible with traditional file-by-file AI assistants.

The learning curve is gentle if you're coming from VS Code. Start with Tab completions and Chat, then graduate to Composer and Agent mode as you develop intuition for what works well. The .cursorrules file is your main lever for customizing behavior, so invest time in getting it right.

Combined with DeployHQ for automated deployments, you get a workflow where features flow from natural language description to production with minimal friction. This is the productivity gain that AI-assisted development has been promising—and Cursor delivers.

Ready to try it? Download Cursor from cursor.com, import your VS Code settings, and start with something simple: open a project and ask "What does this project do?" Then try Cmd+K on a function and ask it to add error handling. Build from there as you learn how Cursor interprets your requests and understands your codebase.