Core Introduction to Full-FREE-SEO-TOOL

This project is an open-source full-stack SEO tool built on Next.js 16. Its core features include:

1. Technical SEO crawler audit
2. Real-time Google Search Console (GSC) data analysis
3. Multi-model AI recommendation generation (supports four platforms: Anthropic, OpenAI, Gemini, OpenRouter)

It aims to break the functional fragmentation of traditional SEO tools and provide operators with a one-stop solution that supports self-hosting and customization.

Project Background

In the AI search era, traditional SEO tools are often limited to single functions (technical audit/rank tracking/content suggestions). This tool is positioned as an integrated platform that deeply combines technical crawlers, GSC data, and AI recommendations.

Basic Tech Stack

• Frontend framework: Next.js 16.2 (App Router architecture + Turbopack)
• Database: SQLite + Prisma 7 ORM
• Core features: Lightweight deployment, complete functionality

Technical Architecture

• Frontend: React19 + Tailwind CSS v4 + shadcn/ui components; charts use recharts; PDF export uses @react-pdf/renderer
• Backend: SQLite (Prisma adapter); authentication uses bcryptjs + jose JWT (stored in HTTP-only Cookie)
• Crawler engine: Uses cheerio for HTML parsing, native fetch requests, and follows robots.txt and rate limits

Nine Audit Analyzers

1. Meta tags/title structure/internal links/external links analysis
2. Image optimization/structured data/security performance analysis
3. Robots protocol/sitemap parsing

Scoring System

Scores independently in four dimensions: technical SEO, page optimization, content quality, and UX performance, then generates a comprehensive health score

GSC Integration

• Authorization method: OAuth2.0 guided configuration
• Data acquisition: Directly calls Search Console v3 API (reduces bundle size)
• Dashboard features: KPI cards (impressions/clicks/CTR/rank), 28-day trend chart, query/page performance tables, manual refresh

AI Recommendation System

• Multi-model support: Anthropic Claude, OpenAI, Gemini, OpenRouter (seamless switching)
• Intelligent recommendation types:
  • Audit report enhancement (executive summary/optimization roadmap/KPI plan)
  • GSC data analysis (potential keywords/low CTR diagnosis/title rewriting/content expansion/internal link mining)
• Flexible configuration: Keys stored locally; OpenRouter supports PKCE OAuth one-click authorization

Application Scenarios

1. New site audit: Input domain to scan and generate a 9-dimension report; AI converts technical issues into business language
2. Content optimization: Identify low CTR pages via GSC; AI generates title/description improvement plans
3. Competitor monitoring: Scan competitors' public pages to analyze technical SEO strategies

Deployment Thresholds

• Local development: Node.js environment; run npm install; only need to set the JWT_SECRET variable
• Production deployment: Single instance is suitable for SQLite; multi-instance requires migration to PostgreSQL/MySQL (Prisma supports seamless migration)

Evolution Direction (Roadmap)

• GA4 integration/PageSpeed Insights API/URL Inspection API
• Scheduled snapshots/keyword rank tracking/team collaboration features

Summary

This project adopts a pragmatic open-source approach. Instead of competing with commercial tools in data breadth, it focuses on deep integration of core functions. The multi-model AI architecture is forward-looking; the MIT license supports community secondary development, making it suitable for technical SEO practitioners and operation teams to self-host.