Open SourceFII/DII Data
    Institutional flow dashboardNode.js / Express / HTML SPA

    FII/DII Data.

    Live dashboard for tracking Foreign Institutional Investor (FII/FPI) and Domestic Institutional Investor (DII) flows in Indian equity markets. Covers cash-market flows, F&O positioning, flow analytics with smart filters, NSDL sector allocation for 24 sectors, and full documentation — all backed by an Express server with cron-scheduled NSE data fetching.

    View on GitHubInstallation Guide

    What the README tells you

    The README documents a 5-tab dashboard system (Home, F&O Positions, Flow Analytics, Sectors, Docs) with detailed feature descriptions, API endpoint reference (6 endpoints), project structure, quick-start commands including seed scripts, data-flow architecture, security headers, and an Agentic AI roadmap for 2026. The live dashboard is at fii-diidata.mrchartist.com.

    Features

    What this repo gives you.

    A quick practical feature map before you open the source code.

    Hero card with FII/FPI Net vs DII Net, flow strength meter, streak trackers, and 45-day heatmaps.

    F&O Positions tab — sentiment badge, OI breakdown by instrument, long/short ratio bars, and 20-period historical positioning chart.

    Flow Analytics — interactive bar charts with 8-month history, daily/weekly/monthly/annual sub-tabs, smart filters (FII Bloodbath, DII Absorption, Extreme Divergence), date-range filter, CSV export, and expandable row details.

    Sectors — 24 NSDL sector cards with AUM %, FII ownership %, sparkline charts, zoom modal with 24-fortnight trend, and toggleable bar/line/scatter views.

    Express backend with cron scheduler, 6 REST API endpoints (/api/data, /api/history, /api/history-full, /api/sectors, /api/market, /api/status), and POST /api/refresh.

    PWA support with service worker, Telegram bot integration for alerts, PM2-ready deployment, and full security headers.

    Installation

    Step-by-Step Setup.

    Follow these steps to get FII/DII Data 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
    1

    Clone

    Start here

    Clone the repository from GitHub.

    2

    Install

    Run npm install to install Express and all dependencies.

    npm install
    3

    Seed data

    Seed historical data. node scripts/seed_history.js and node scripts/seed_sectors.js (first time only).

    node scripts/seed_history.js && node scripts/seed_sectors.js
    4

    Start server

    Start the server. npm start — runs on http://localhost:3000.

    npm start
    5

    Dev mode

    For development with auto-reload. npm run dev.

    npm run dev
    6

    Deploy

    Production

    For production (Hostinger/VPS). NODE_ENV=production node server.js or use PM2: pm2 start server.js --name fii-dii.

    NODE_ENV=production node server.js && pm2 start server.js --name fii-dii
    Want AI to do this for you?Copy a ready-made prompt for Antigravity, Codex, or Claude below ↓
    AI-Powered Setup

    Set Up FII/DII Data 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/fii-dii-data. 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 the seed scripts first to populate historical data, then start the server and explore each tab to understand the 5-tab architecture before making changes.

    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/fii-dii-data. 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 the seed scripts first to populate historical data, then start the server and explore each tab to understand the 5-tab architecture before making changes.

    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/fii-dii-data 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 data pipeline: NSE India API → server.js cron → data/history.json → /api/* endpoints → public/index.html. Ask it to explain the 5-tab architecture and how each tab fetches data from the Express API. Ask it to trace the Flow Strength Meter formula, Momentum Alpha calculation, and streak logic. Ask it to identify the sector data flow: NSDL FPI Reports → seed_sectors.js → data/sectors.json → /api/sectors. Ask it to add one focused feature: a new smart filter, a Telegram alert trigger, or a custom date-range view.

    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
    01

    Map the data flow

    Ask the AI to map the data pipeline: NSE India API → server.js cron → data/history.json → /api/* endpoints → public/index.html.

    02

    Explain the architecture

    Ask it to explain the 5-tab architecture and how each tab fetches data from the Express API.

    03

    Trace the logic

    Ask it to trace the Flow Strength Meter formula, Momentum Alpha calculation, and streak logic.

    04

    Map the data flow

    Ask it to identify the sector data flow: NSDL FPI Reports → seed_sectors.js → data/sectors.json → /api/sectors.

    05

    Make one focused change

    Ask it to add one focused feature: a new smart filter, a Telegram alert trigger, or a custom date-range view.

    Best Next Step

    Run the seed scripts first to populate historical data, then start the server and explore each tab to understand the 5-tab architecture before making changes.

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