On Page SEO

On-Page SEO Analyzer - Analyze your website's SEO performance

Digital Marketing & SEOTypeScriptMIT

Abstract

On Page SEO is an open-source Digital Marketing & SEO project. On-Page SEO Analyzer - Analyze your website's SEO performance. A comprehensive on-page SEO analysis tool that helps you audit and optimize your website's SEO performance. Analyze up to 500 pages at once with detailed insights on 74 SEO metrics. It is built using TypeScript. Key capabilities include: Page Discovery: Automatically discover pages on your website using Firecrawl; Comprehensive Analysis: Analyze 74 SEO metrics per page using DataForSEO; Core Web Vitals: Track LCP, FID, and CLS scores. The complete source code is publicly available on GitHub under the MIT License, making it a useful reference for students building a Digital Marketing & SEO mini project or final-year project.

1. Introduction

A comprehensive on-page SEO analysis tool that helps you audit and optimize your website's SEO performance. Analyze up to 500 pages at once with detailed insights on 74 SEO metrics.

2. Objective

On-Page SEO Analyzer - Analyze your website's SEO performance

This project demonstrates how TypeScript can be applied to a real-world Digital Marketing & SEO problem.

3. Key Features / Modules

  • Page Discovery: Automatically discover pages on your website using Firecrawl
  • Comprehensive Analysis: Analyze 74 SEO metrics per page using DataForSEO
  • Core Web Vitals: Track LCP, FID, and CLS scores
  • Real-time Progress: Watch your audit progress with live updates
  • Export Results: Download reports as CSV or JSON
  • Dark Mode: Full dark mode support

4. Technology Stack

TypeScript
  • React 19 with TypeScript
  • Vite for blazing fast builds
  • TanStack Router & React Query
  • Tailwind CSS with Shadcn/ui components
  • Recharts for data visualization
  • Node.js with Express
  • SQLite database (better-sqlite3)
  • TypeScript

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

  • Node.js (LTS) and npm / yarn / pnpm
  • VS Code or any code editor
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/AgriciDaniel/on-page-seo.git
cd on-page-seo
# Install all dependencies (root, client, and server)
npm run install:all

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

  • Export reports to Google Sheets or PDF
  • Schedule weekly automated reports
  • Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

  1. Which marketing or SEO problem does this tool solve?
  2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
  3. Which metrics or KPIs does it report and how are they calculated?
  4. How could the output help a business make decisions?
  5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by AgriciDaniel and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.

View Source on GitHubDownload ZIP

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