Mock API Builder

A lightweight mock backend + mock database built for Frontend Developers — no backend knowledge required.
Create data models, generate mock data, and call real REST APIs instantly while focusing entirely on UI development.

✨ Features

• Create Projects and organize your mock data
• Define Resources (tables/collections) like users, products, posts, etc.
• Add Fields with supported types:
  • string
  • number
  • boolean
  • date
  • faker (auto-generate realistic test data)
• Switch Data Mode:
  • Schema Mode — simple structured fields
  • JSON Template Mode — supports complex nested objects/arrays
• Clean, RESTful dynamic API endpoints

🎯 Designed For

• Frontend devs learning React / Vue / Svelte / Next.js
• Rapid UI prototyping without backend setup
• Portfolio / demo / hackathon projects
• Teams who need mock data that actually looks real

🏗 Tech Stack

Layer	Technology	Reason
Backend	NestJS	Scalable, clean architecture
ORM	Prisma	Strong Postgres + DX
Database	PostgreSQL (JSONB)	Flexible schema, no heavy migrations needed
Auth	JWT	Works anywhere, simple integration
Mock Data	Faker.js	Generate realistic sample data

🧱 Backend Roadmap (Detailed)

Area	Task	Status	Notes
Auth / Users	JWT authentication	✅ Done	Core login / identity functional
	Authorization per project/resource	✅ Done	Owner-based access enforced
Projects	Create / List / Delete projects	✅ Done	Workspaces structured
	Project metadata (stats, updatedAt)	🔜	Optional for dashboard summary
Resources	Create / List / Delete resources	✅ Done	Logical data tables
	Get Resource detail (for schema UI)	✅ Done	Returned with fields included
	Rename resource	🔜	Improves DX and data clarity
Fields (Schema)	Add / Edit / Delete fields	✅ Done	Field-level schema control
	Support fakerType when type = faker	✅ Done	Enables controlled fake data
	JSON Template mode support (backend storage)	✅ Done	resource.mode + resource.jsonTemplate added
	Validate template syntax on save	🔜	Avoid invalid generation errors
Records (Data Layer)	Store record as JSONB (Record.data)	✅ Done	Model supports any structure
	CRUD API for records	✅ Done	/records service + validation rules
	Pagination + sorting	🔜	Prevent performance issues on large sets
	Validation against schema/JSON Template	🔜	Ensures consistent dataset shape
Mock Data Generation	Faker-based generation service	✅ Done	Used when mode = schema
	Recursive generator for JSON Template	🔜	Supports nested objects / arrays
	Background/bulk generation job	🔜	Needed for large count values
Public REST API	Dynamic CRUD endpoint → /api/:project/:resource	✅ Done	Core feature for FE integration
	Dynamic CRUD detail → /api/:project/:resource/:recordId	✅ Done	For item-level view/edit
	Error responses + validation contracts	🔜	Ensure consistent DX for frontend devs
API Access Control	API Keys (generate, revoke, list)	🔜	Allows calling API without JWT
	Token-based access to dynamic API	🔜	Required for embedding into frontend apps
	Rate limit per plan (Free vs Pro)	🔜	backend-level enforcement (likely Upstash)
Export / Integration	Export resource schema → Supabase SQL	⭐ Planned	Converts our metadata → Postgres tables
	Export records → Supabase INSERT batches	⭐ Planned	Moves mock → real data without rewriting FE
Performance / Infra	Index Record.resourceId	✅ Done	Enables fast record filtering
	Query optimization (limit, projection)	✅ Policy ready	Default pagination avoids large payloads
	Optional Redis cache for GET list	🔜	Only needed >2k users or heavy load
Quality / Tooling	DTO validation (class-validator)	✅	Framework-level input validation
	Consistent error handling (global filter)	✅	Proper structured errors
	Logging & request tracing	🔜	Helps debugging dynamic API behavior

🔜 Next Steps (In Progress)

• Webhooks Integration — Enhanced log filtering and test payloads
• Export resource schema → Supabase SQL
• AI-Assisted Data Generation
• API Keys for secured external access
• Pagination & Sorting for large datasets

🌱 Future Enhancements

• AI-Assisted Data Generation
  • Describe your dataset → AI builds schema + mock data
• Code Snippet Generator
  • Auto-generate usage snippets for:
    • React
    • Vue
    • Svelte
    • Axios / Fetch / TanStack Query
• One-Click Export to Supabase
  • Convert mock DB → real Postgres tables instantly
  • Keep the same frontend code

🚀 Getting Started

Follow these steps to set up and run the project locally.

1. Prerequisites

• Node.js (v18 or higher recommended)
• npm or yarn

2. Environment Setup

Create a .env file in the root directory and add the following variables:

VITE_API_BASE_URL=http://localhost:3002/api/v1
VITE_API_BASE_MOCK_URL=http://localhost:3002/api/v1
VITE_GOOGLE_CLIENT_ID=your-google-client-id
VITE_GITHUB_CLIENT_ID=your-github-client-id

3. Installation

Install the project dependencies:

npm install
# or
yarn install

4. Running the Project

Start the development server:

npm run dev
# or
yarn dev

The application will be available at http://localhost:5173.

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🧭 Philosophy

Focus on UI, not backend. Data should be easy to create, realistic to display, and effortless to integrate.

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🚀 Status

The project foundation is complete and stable. Dashboard features including Project Management, Resource Schema Definition, Mock Data Generation, and Records Management are fully functional.

Webhooks support is also live, allowing you to capture and inspect incoming requests.

We are currently focusing on Schema Export and Advanced Data Generation features.

Stay tuned ✨