Cursor vs MainFunc
A detailed side-by-side comparison to help you choose the right AI coding agent for your needs.
Best overall for flow and speed
Cursor
Cursor is an AI-native code editor built as a fork of VS Code, designed from the ground up for AI-powered development. Its standout feature is Composer, an agentic system that can edit multiple files ...
AI Models
Claude Sonnet 4.5GPT-5.3Gemini 3 ProCustom models
Key Features
- Composer agent for multi-file editing with full project context
- Up to 8 parallel agents in isolated git worktrees
- 10+ specialized tools: semantic search, file operations, terminal, browser
- Multi-file refactoring across 12+ files in single operation
- Full VS Code compatibility with extensions support
Pricing
Hobby — $0/month
Pro — $20/month
Business — $40/user/month
Pro+ — $60/month
Ultra — $200/month
Pros
- Fastest multi-file editing with parallel agents
- VS Code compatibility means zero learning curve
- Isolated worktrees prevent conflicts during experimentation
Cons
- Premium tiers required for advanced features
- Resource-intensive with multiple agents running
Best platform for building and deploying custom enterprise AI agents
MainFunc
MainFunc is an AI platform for building, deploying, and managing custom enterprise agents that automate complex business workflows requiring code generation, system integration, and multi-step reasoni...
AI Models
GPT-4oClaude Opus 4.6Claude Sonnet 4Gemini 1.5 ProCustom fine-tuned models
Key Features
- Visual agent builder with reusable action blocks for business logic
- Managed execution layer handling orchestration, retries, and error recovery
- Sandboxed code execution environment for agents writing and running code
- Real-time execution traces and token usage analytics per workflow
- Multi-model support with per-step model selection
Pricing
Developer — Contact for pricing
Team — Contact for pricing
Enterprise — Custom pricing
Pros
- Production-grade execution layer removes infrastructure burden from engineering teams
- Visual builder accelerates agent development without sacrificing customization
- Per-step model selection optimizes cost and capability across complex workflows
Cons
- Best suited for engineering teams; requires technical configuration for complex agents
- Pricing requires sales engagement with no fully self-serve tier