Install
Start hereInstall Node.js v18+ (recommended v20+).
Open SourceFunda Scanner
Fundamental research platformReact 18 + Vite + TypeScript + Tailwind CSS + shadcn/ui + Recharts
Funda Scanner.
Bloomberg-terminal-inspired fundamental analysis platform for 2,229+ NSE-listed companies. Ships with realistic mock data for 20 blue-chip NSE companies and is designed to connect to any backend API. Features 9 pages, 73 components, 7 custom hooks, TradingView Scanner API integration for live screener data, and a full design system with dark/light themes, accent color customization, and density settings.
What the README tells you
31 ⭐ | 14 forks | 99 commits | MIT licensed. The README documents a comprehensive architecture diagram (Client → Lib Layer → Vite Dev Proxy → TradingView/Backend), 9 page routes, 24 company analysis sections, full project structure tree with 73 components, backend integration guide with 3 API endpoints, TradingView proxy config, PWA support, and Playwright E2E test configuration.
Features
What this repo gives you.
A quick practical feature map before you open the source code.
Dashboard — Live Market Ticker (6 indices with sparklines), Market Overview (total market cap, breadth, avg ROCE/ROE/D-E), Fundamental Movers (YoY ROCE change leaders), Quality Compounders (ROCE>15%, ROE>12%, D/E<0.5), Value Picks (PE<25, ROCE>10%), Sector Heatmap (11 sectors), FII/DII Flow Tracker, IPO Calendar, Top Gainers/Losers/Most Active, drag-to-reorder customizable layout.
Stock Screener — Real-time TradingView Scanner API integration, custom filter builder with AND logic, 16 screening metrics (Market Cap, PE, EPS, ROCE, ROE, D/E, Dividend Yield, FCF Yield, etc.), 13 pre-built presets (Large Cap, High ROCE, Low Debt, Growth Stocks, etc.), CSV export, save custom screens.
Company Deep-Dive — 24 analysis sections: Header, Key Ratios Grid, Fundamental Scoring, Pros & Cons, Interactive Price Chart (1Y OHLCV), Analyst Ratings, Quarterly Results, 10-year Financial Statements (P&L/BS/CF), Cash Flow Quality, Ratio Trend Analysis, Shareholding Pattern (8-quarter trend), Revenue Segmentation, MF Holdings, Insider Deals, Management Info, Dividend Analysis, Documents, Corporate Actions, Peer Comparison, PDF/CSV Export.
Compare Tool — Side-by-side comparison of any two stocks with visual indicators across all key metrics.
DCF Calculator — Full Discounted Cash Flow valuation model with adjustable growth rate, discount rate, terminal growth, intrinsic value + margin of safety.
Portfolio Tracker + Watchlist — Add holdings with purchase price/quantity, track P&L and sector diversification. Quick-access watchlist with live prices.
UX — Dark/Light theme (system-aware), Accent Color Picker (runtime customization persisted in localStorage), 3 density modes (compact/comfortable/spacious), Command Palette (⌘K), keyboard shortcuts, onboarding tour, Framer Motion page transitions, mobile-responsive with bottom nav, PWA ready.
Installation
Step-by-Step Setup.
Follow these steps to get Funda Scanner running on your machine.
Setup Path
Run it locally, then inspect the system.
Follow the README flow first. Once the app opens locally, use the AI prompts below to trace the data flow and make focused changes.
CloneInstallRunInspect
Clone
Clone. git clone https://github.com/MrChartist/Funda-Scanner-Base-Project.git && cd Funda-Scanner-Base-Project
git clone https://github.com/MrChartist/Funda-Scanner-Base-Project.gitInstall
Install. npm install (or bun install).
npm install && bun installDev mode
Start dev server. npm run dev — opens on http://localhost:8080 with HMR.
npm run devConfigure
(Optional) Connect a backend: create .env with VITE_API_URL=https://your-backend-api.com — the app's src/lib/api.ts expects /api/company/:symbol/intelligence, /api/search?q=query, and /api/market/dashboard.
Deploy
For production. npm run build outputs to dist/, then npm run preview to test.
Step 7
ProductionRun tests. npm run test | npm run test:watch. Lint: npm run lint.
AI-Powered Setup
Set Up Funda Scanner With AI.
Pick your AI tool, copy the prompt, and let it handle the entire setup and codebase walkthrough for you.
Google Antigravity
Best when you want the assistant to operate inside the editor and handle setup end-to-end.
Desktop editorGitNode or PythonModel access
Ready-to-use prompt ↓
Open https://github.com/MrChartist/Funda-Scanner-Base-Project. Clone the repository, inspect the README first, then set up the project locally using the exact setup steps from the README. Before editing anything, explain the stack, folder structure, data flow, required environment variables, and the safest first customization for this project: Run npm run dev, explore the mock data dashboard, then ask an AI to trace the TradingView proxy integration in the Screener before connecting a live backend.
How it works: Paste the prompt into Antigravity after choosing the repo. Ask it to read the README first, run setup commands, keep changes small, and explain every file it touches before editing.
OpenAI Codex
Best when you want command-by-command setup, debugging, code edits, and verification in a local workspace.
GitTerminalNode or PythonLocal workspace
Ready-to-use prompt ↓
I want to work on https://github.com/MrChartist/Funda-Scanner-Base-Project. First read the README and summarize what the project does. Then give me the exact commands for my operating system to clone, install, configure environment variables, and run it locally. After it runs, inspect the codebase and propose one small change that matches this goal: Run npm run dev, explore the mock data dashboard, then ask an AI to trace the TradingView proxy integration in the Screener before connecting a live backend.
How it works: Paste the prompt into Codex with the repository URL. Ask it to run the project, identify the stack from files instead of guessing, make scoped edits, and verify with build or browser checks.
Claude
Best when you want architecture explanation, codebase understanding, and a clean implementation plan before edits.
Repo accessREADME contextTerminal if using Claude Code
Ready-to-use prompt ↓
Analyze https://github.com/MrChartist/Funda-Scanner-Base-Project from the README and source structure. Create a clear architecture map, explain the main modules, identify setup risks, and recommend a safe implementation plan for extending it. Focus especially on: Ask the AI to map the architecture: Pages (9 routes) → Components (73) → Hooks (7) → Lib Layer (mock-data/api/tradingview/export-utils) → Vite Dev Proxy (/api/tv → scanner.tradingview.com). Ask it to trace how the Screener page uses TradingView Scanner API via the Vite proxy for live NSE data, and how custom filters map to TradingView field names. Ask it to explain the 24-section CompanyDetail.tsx rendering flow, the section() helper pattern, and how CompanyPageNav.tsx provides sidebar navigation. Ask it to show how to replace getMockCompanyIntelligence(symbol) calls with the api.getCompanyIntelligence(symbol) backend client for live data. Start with one focused change: add a new screener metric to the METRICS array, add a new company analysis section, or customize the design tokens in src/index.css.
How it works: Paste the prompt with the GitHub link. Ask Claude to read the README, map modules, list risks, and produce a practical plan before using Claude Code or another agent to implement.
AI Focus
What to Ask the AI.
After setup, use these focused questions to get the most value from your AI assistant.
AI Briefing Mode
Ask for maps, not magic.
Use these prompts after the repo runs locally. The goal is to make the AI trace the system before it changes code.
FlowLogicRiskChange
Explain the architecture
Ask the AI to map the architecture: Pages (9 routes) → Components (73) → Hooks (7) → Lib Layer (mock-data/api/tradingview/export-utils) → Vite Dev Proxy (/api/tv → scanner.tradingview.com).
Prompt 2
Ask it to trace how the Screener page uses TradingView Scanner API via the Vite proxy for live NSE data, and how custom filters map to TradingView field names.
Prompt 3
Ask it to explain the 24-section CompanyDetail.tsx rendering flow, the section() helper pattern, and how CompanyPageNav.tsx provides sidebar navigation.
Prompt 4
Ask it to show how to replace getMockCompanyIntelligence(symbol) calls with the api.getCompanyIntelligence(symbol) backend client for live data.
Make one focused change
Start with one focused change: add a new screener metric to the METRICS array, add a new company analysis section, or customize the design tokens in src/index.css.
Best Next Step
Run npm run dev, explore the mock data dashboard, then ask an AI to trace the TradingView proxy integration in the Screener before connecting a live backend.