Kombai: The AI Agent Built for Frontend Development

Frontend is unforgiving pixel perfection, component constraints, type safety and the endless grind of browser debugging. Generic coding agents talk a big game but stumble on real‑world UI and repo context.

Kombai changes that: a domain‑specific agent engineered solely for the frontend, built with a specialised context engine and tooling.

It reads Figma, understands component libraries, plans complex tasks, generates code, auto‑runs locally and fixes errors before touching the repo.

From landing pages to complex app UIs, it delivers clean, backend‑agnostic code right inside the IDE fast.

The outcome: higher fidelity, fewer regressions, accelerated ship cycles and confident frontend flow.

Task focus,

• Traditional Coding Agents: General-purpose; weak on complex UI tasks
• Kombai: Frontend‑specific agent; optimized context + tooling for UI[](https://kombai.com/why)

Fidelity to Figma

• Traditional Coding Agents: Inconsistent; misses components/props,
• Kombai: Built-in models code real Figma designs with unmatched fidelity

Codebase understanding

• Traditional Coding Agents: Embedding search misses domain context,
• Kombai: Human‑like repo understanding; indexes components, configs, props

Planning

• Traditional Coding Agents: Minimal or generic plans,
• Kombai: Editable, task‑aware plans for complex tasks

Compile rate

• Traditional Coding Agents: Variable; frequent TypeScript/lint failures,
• Kombai: Auto‑fixes linting/TS errors; higher successful compile rate

Runtime feedback

• Traditional Coding Agents: Limited or manual loops,
• Kombai: Sandbox server + visual preview for large UI tasks

Safety

• Traditional Coding Agents: May write unintended changes, Kombai: Never writes until explicitly saved; safe iteration

IDE workflow

• Traditional Coding Agents: Chat-first assistants,
• Kombai: Generates, runs, previews and saves inside the IDE

Stack usage

• Traditional Coding Agents: Struggles with custom libraries,
• Kombai: Uses supported libraries with specific, human-tested RAGs

Performance vs frontier models

• Traditional Coding Agents: Typically benchmarked on non-frontend tasks,
• Kombai: Demonstrated better pass/verification/compile outcomes in internal comparisons on frontend tasks.

Real metrics: Kombai highlights higher “% review criteria passed,” “% features verified,” and “% outputs compiled successfully” against Gemini 2.5 and Sonnet 4 agent setups (with/without MCPs) in its published comparison for real‑world frontend tasks.

Context note: SWE-bench style benchmarks skew to simple bug fixes, not complex frontend, which explains general agents’ gaps and Kombai’s specialisation advantage.

• Product positioning: “The best agent for real‑world Frontend tasks,” with strong outcomes on fidelity, code quality and dev velocity across Figma/text/image inputs.
• Comparative testing: Kombai’s site shows superior pass rates, feature verification and successful compile rates vs Gemini 2.5 Pro and Sonnet 4 agents (with/without MCPs) in frontend tasks; agents used include Aider/OpenAI agent + CodeMCP/Filesystems MCP and MCPs like Context7/Framelink.
• Public reception: Product Hunt listing describes Kombai as “the first domain‑specific AI for frontend tasks beyond prototypes,” focused on building entire app UIs and outperforming generic agents.
• Security & enterprise: SOC 2 certified; no training on user data; custom context‑engines for complex enterprise stacks.

Kombai isn’t just another IDE add‑on, it’s an agentic system optimised for frontend.

Core capabilities

• Generate code from Figma, images, or text inputs.
• Build editable, domain‑specific plans before complex tasks; update via natural language.
• Auto‑fix linting/TypeScript errors; send runtime errors directly from the browser workflow.
• Run a sandbox server for visual previews; save only when approved, ensuring safe iteration.
• Indexed search for frontend codebases; component library indexing; stack configuration with supported libraries via human‑tested RAGs.

Spec

Languages/Targets

• Frontend code generation; supports TypeScript/JS patterns; clean, backend‑agnostic output

Inputs

• Figma links, images, text prompts

IDEs

• VS Code, Cursor, and Windsurf extensions available via sidebar integration

Modes

• Code mode (generation), Ask mode (search/understand codebase)

Planning

• Editable markdown plan files; task‑aware (schemas/enums/endpoints for apps; colors/fonts/animations for marketing pages)

Execution

• Auto‑run locally with sandbox server preview; visual iteration loop

Error handling

• Auto‑fix linting/TS; easy runtime error feedback to agent

Safety

• No writes until explicit save

Context engine

• Human‑like repo understanding; indexes components/configs/props; specialised RAGs for supported libraries

Security

• SOC 2; no training on customer data

Sample I/O Table

Prompt/Input: Figma link for dashboard page with table, filters and dark mode

• Kombai Plan/Response: Generates an editable plan covering sections (header/sidebar/table/filters), component choices (Table, Select, Toggle), theming tokens, accessibility notes and animation hooks; after approval, produces TSX/CSS modules with data fetch placeholders, runs preview, fixes TS/lint automatically and offers save‑ready diffs.

Prompt/Input: “Build marketing hero with gradient background, animated CTA, responsive grid”

• Kombai Plan/Response: Plan outlines fonts, colors, animation timing and responsive breakpoints; outputs production‑ready markup/styles; launches preview; iterates via natural language (“tighten letter‑spacing; slow CTA pulse”).

Documentation hub: Official Documentation Page 

Quickstart and guides: Generate from Figma, configure stack, plan, run, view/save.

Extension distribution: Available for VS Code/Cursor/Windsurf.

Product discovery: Product Hunt page highlighting positioning and community interest.

Note: Kombai’s primary assets are proprietary; no open‑source license is listed for the agent itself in official materials.

Creator channels and reviews: Multiple developer reviews on YouTube showcasing real usage and positive outcomes in complex UI scenarios.

Install in the IDE

• VS Code/Cursor/Windsurf: Install Kombai extension; find it in the primary sidebar; optionally move to secondary sidebar for a smoother split‑view workflow.

Sign‑in

• Click “Sign In” in the extension; complete account auth on the website; redirected back to IDE.

Quickstart flow

• Open Kombai in IDE - add Figma/text/image input - Send - review generated plan - Approve Plan & Start Coding - auto‑run local preview - View & Save to write selected files.

Modes to know

• Code mode for generation; Ask mode for repo search/understanding.

System requirements

• Runs inside supported IDEs with a local dev environment capable of running the preview server; follows typical frontend project prerequisites (Node/PNPM/Yarn as applicable to repo).

Key guides

• Generate from Figma: end‑to‑end workflow with fidelity emphasis.

• Plan for complex tasks: editable markdown, natural‑language updates.

• Free: $0; 200 credits (+300 limited‑time offer) for light, personal exploration.
• Plus: $20/month; 2,000 credits/month.
• Pro: $40/month; 4,200 credits/month.
• Premium: $100/month; 11,000 credits/month.

For more details Visit Pricing 

Q1. What makes Kombai different from general coding assistants?

Kombai is a domain‑specific agent for frontend with a custom context engine, specialised RAGs, editable planning, compile/error‑fix loops and sandbox previews purpose‑built for UI work.

Q2. Can Kombai convert Figma designs into production‑ready code?

Yes, it's built‑in models code real Figma designs with high fidelity and supported library awareness, generating clean, backend‑agnostic output.

Q3. How does Kombai handle errors?

It auto‑fixes linting/TypeScript errors and supports easy runtime error reporting from the browser, improving successful compile rates.

Q4. Which IDEs are supported?: VS Code, Cursor and Windsurf with native sidebar integration.

Q5. How do I start quickly?

Open the extension, add Figma/text/image input, approve the plan, let it generate and run locally, iterate, then View & Save.

Q6. Is Kombai suitable for enterprises?

Yes, SOC 2, no training on customer data and custom context engines for complex stacks.

Try Kombai Today.

Get started at Kombai and dive into the docs.

Pick a plan that fits from Free to Premium at Pricing 

Fast‑track frontend from messy debug sessions to AI‑powered clarity. Level up from junior to senior dev, ship cleaner code, faster, with confidence.

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