Claude Code vs Cursor: A Monorepo Showdown
A real-world comparison of Claude Code and Cursor when building complex features in a large monorepo, exploring their strengths and limitations.
The AI-assisted development landscape has evolved rapidly, with tools like Claude Code and Cursor promising to revolutionize how we build software. As someone who's used both extensively, I wanted to put them head-to-head in a real-world scenario: building an admin dashboard feature in a complex monorepo. The results were eye-opening.
The Testing Ground: A Complex Monorepo
My test environment was a production monorepo with:
- 9+ interconnected packages with shared dependencies
- Comprehensive .cursorrules and .mdc files detailing project architecture, conventions, and patterns
- GraphQL schema with complex nested types
- Custom routing system with configuration-driven page generation
- Repository pattern for data access with type-safe GraphQL operations and code generation
The task was simple in concept but complex in execution: create a standard admin page following the existing architecture patterns.
Round 1: Claude Code with /init
Claude Code's approach starts with the /init command, which analyzes your codebase and creates a CLAUDE.md file to guide future interactions.
The Setup Process
# Claude Code initialization
$ claude
$ /init
The initialization was thorough, scanning the entire monorepo and creating a comprehensive CLAUDE.md.
The Implementation Attempt
Armed with the CLAUDE.md documentation, I asked Claude Code to create a new admin page for managing "absence reasons".
The Struggles
Despite having detailed documentation, Claude Code struggled with:
- Context Navigation: Difficulty jumping between related files across the monorepo
- Pattern Recognition: Missed subtle but important architectural patterns
- Configuration Understanding: Couldn't grasp the config-driven page generation system
- Error Recovery: When initial approach failed, subsequent attempts made things worse
The process took a long time with multiple back-and-forth iterations, and the final result still had integration issues.
Round 2: Cursor with .cursorrules and .mdc files
Cursor's approach relies on .cursorrules and .mdc files that provide context about your project's architecture and conventions.
The Implementation
I gave Cursor the exact same request: "Create an admin page for absence reasons following the existing patterns."
The entire implementation took 8 minutes and worked perfectly on the first try.
The Key Differences
Architecture Understanding
Claude Code: Despite having access to the full codebase and generated documentation, it struggled to understand the interconnected nature of the monorepo architecture. It often treated each file in isolation.
Cursor: With well-crafted .cursorrules and .mdc files, it immediately grasped the config-driven approach and repository pattern, implementing everything cohesively.
Error Handling and Recovery
When Claude Code made mistakes, it often compounded them in subsequent attempts. Cursor, with its better context understanding, rarely needed correction.
Performance Metrics
| Metric | Claude Code | Cursor |
|---|---|---|
| Setup Time | 9 minutes (/init) | 0 minutes (existing .cursorrules, .mdc files) |
| Implementation Time | 16 minutes | 8 minutes |
| Errors Generated | 12+ | 0 |
| Manual Fixes Needed | 8 | 0 |
| Files Modified | 8 | 8 |
| Final Result | Partially working | Production-ready |
Why the Difference?
Context Scope
Claude Code generates documentation from the entire codebase but struggles with the dynamic context needed for complex implementations. The CLAUDE.md file, while comprehensive, is static.
Cursor with .cursorrules and .mdc files maintains active context about patterns and conventions, making it more effective for complex, interconnected features.
Documentation vs. Rules
The instruction-based approach of .cursorrules and .mdc files proved more effective for guiding implementation.
When Each Tool Excels
Claude Code Strengths
- Scoped Features: Excellent for building isolated components or utilities
- Code Analysis: Superior at analyzing and explaining existing code
- Documentation: Great for generating documentation and explanations
- Learning: Better for understanding new codebases and technologies
Cursor Strengths
- Complex Architecture: Excels in established, complex codebases
- Pattern Following: Superior at adhering to existing conventions
- Speed: Much faster for standard implementations
- Integration: Better at understanding interconnected systems
Recommendations
Use Claude Code When:
- Building new features with clear boundaries
- Analyzing or documenting existing code
- Working on smaller, focused projects
- Learning new technologies or patterns
Use Cursor When:
- Working in established, complex codebases
- Following existing architectural patterns
- Building features that integrate with many systems
- Speed is critical for delivery
The Verdict
Both tools have their place in the modern development workflow, but they serve different purposes:
Claude Code is like having a knowledgeable consultant who can analyze your codebase and provide insights, but may struggle with complex implementations in large, interconnected systems.
Cursor is like having a team member who's already familiar with your codebase and can immediately start building following established patterns.
For complex monorepos with established architectures, Cursor currently has a significant advantage. However, as Claude Code evolves and improves its context handling, this gap may narrow.
The key lesson: choose your AI assistant based on the complexity and maturity of your codebase. Both tools are powerful, but understanding their strengths will help you maximize their effectiveness in your development workflow.
Looking Forward
The AI-assisted development space is rapidly evolving. While Cursor currently leads in complex codebase navigation, Claude Code's analytical capabilities and potential for improvement make it an exciting tool to watch.
The future likely belongs to developers who can effectively leverage both tools for their respective strengths, creating a more powerful and flexible development workflow.