SpecDrive

AI-Powered Automotive Parts Data Enrichment Tool

Instantly retrieve complete product specifications, compatibility data, marketing content, and cross-references for any aftermarket automotive part. Perfect for catalog enrichment and product data management.

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Overview

SpecDrive streamlines automotive parts research by leveraging AI to automatically gather and organize product information from across the web. Enter any aftermarket part number and receive structured data including specifications, vehicle compatibility, features, and source references—all in seconds.

Use Case: Companies can use this tool to enrich incomplete product catalog data without hours of manual research.

Features

🔍 Intelligent Part Lookup

• Enter any aftermarket part number (e.g., K&N 33-2304, NGK 3403)
• AI-powered web research extracts comprehensive product attributes
• Displays structured results with technical specifications, dimensions, and materials

⚡ Deep Research Mode

• Toggle between Standard and Deep Research modes
• Standard Mode: Basic specs, compatibility, and features (lower API cost)
• Deep Research Mode: Comprehensive extraction including:
  • Marketing content (short/long descriptions, bullet points, benefits)
  • Cross-reference data (OEM numbers, alternative parts, supersession info)
  • Detailed fitment (engine sizes, trim levels, position/location)
  • UPC codes when available

🚗 Vehicle Compatibility

• Automatic detection of compatible makes, models, and years
• Engine size and trim level specifics (Deep Research)
• Position/location data (front/rear, left/right)
• OEM cross-reference part numbers
• Fitment notes and exceptions

📝 Marketing Content Extraction

• Short descriptions for product listings
• Long descriptions for product pages
• Key selling points and bullet points
• Customer benefits

🔄 Cross-Reference Data

• OEM part numbers this part replaces
• Alternative/interchangeable part numbers from other brands
• Supersession information (older parts replaced, newer replacements)
• UPC/EAN codes

📊 Parts Catalog

• Save researched parts to your local catalog
• Full offline access to saved specifications
• Search and filter your saved inventory
• Expandable cards with complete part details
• Export entire catalog to CSV

📤 Export Functionality

• Single Part Export: Download any researched part as CSV
• Catalog Export: Export all saved parts to CSV for import into PIM systems
• Flattened data structure suitable for spreadsheets and databases

📋 Copy-to-Clipboard

• One-click copy buttons on key fields
• Easily copy descriptions, part numbers, and specifications
• Visual feedback on successful copy

📜 Search History

• Automatic tracking of all part searches
• One-click re-search from history
• Relative timestamps for easy reference
• Individual or bulk clear options

🎯 Data Intelligence

• Source verification with direct links
• Confidence indicators
• Feature highlights and key specifications
• Warranty and installation notes when available

Tech Stack

Layer	Technology
Frontend	React 18, TypeScript, Vite
Styling	Tailwind CSS, clsx, tailwind-merge
Icons	Lucide React
Backend	Node.js, Express.js
AI Engine	Anthropic Claude API with Web Search

Getting Started

Prerequisites

• Node.js 18+
• npm or yarn
• Anthropic API key

Installation

1. Clone the repository

   git clone https://github.com/PeytonNowlin/SpecDrive.git
   cd SpecDrive

2. Install dependencies

   npm install

3. Configure environment variables

   Copy the example environment file and add your API key:

   cp .env.example .env

   Then edit .env and add your Anthropic API key:

   ANTHROPIC_API_KEY=your_api_key_here

4. Start the development servers

   # Start both frontend and backend concurrently
   npm run dev:all

   Or run them separately:

   # Terminal 1 - Backend API server (port 3001)
   npm run server
   
   # Terminal 2 - Frontend dev server (Vite)
   npm run dev

5. Open the application

   Navigate to http://localhost:5173 in your browser.

Scripts

Command	Description
npm run dev	Start Vite development server
npm run server	Start Express backend server
npm run dev:all	Start both servers concurrently
npm run build	Build for production
npm run preview	Preview production build

Project Structure

SpecDrive/
├── src/
│   ├── components/
│   │   ├── Layout/
│   │   │   └── Shell.tsx          # App shell with navigation
│   │   ├── Search/
│   │   │   └── SearchHeader.tsx   # Search input with Deep Research toggle
│   │   └── UI/
│   │       ├── Badge.tsx          # Status badges
│   │       ├── Card.tsx           # Card container
│   │       └── DataGrid.tsx       # Specification grid
│   ├── lib/
│   │   ├── catalog.ts             # Catalog persistence & types
│   │   ├── export.ts              # CSV export utilities
│   │   ├── history.ts             # Search history management
│   │   ├── sanitize.ts            # Data sanitization
│   │   └── utils.ts               # Utility functions
│   ├── pages/
│   │   ├── Catalog.tsx            # Saved parts catalog with export
│   │   ├── History.tsx            # Search history view
│   │   └── PartLookup.tsx         # Main search interface
│   ├── App.tsx                    # Root component
│   ├── index.css                  # Global styles
│   └── main.tsx                   # Entry point
├── server.js                      # Express API server
├── index.html                     # HTML template
├── tailwind.config.js             # Tailwind configuration
├── vite.config.ts                 # Vite configuration
└── package.json

API Reference

POST /api/research

Research an automotive part by part number.

Request Body:

{
  "partNumber": "K&N 33-2304",
  "deepResearch": false
}

Parameter	Type	Default	Description
partNumber	string	required	The part number to research
deepResearch	boolean	false	Enable comprehensive data extraction

Standard Response:

{
  "partNumber": "33-2304",
  "partName": "High-Flow Air Filter",
  "manufacturer": "K&N Engineering",
  "category": "Air Filters",
  "specifications": {
    "Length": "11.438 in",
    "Width": "9.75 in",
    "Height": "1.188 in",
    "Material": "Cotton Gauze"
  },
  "compatibility": {
    "Makes": ["Honda", "Acura"],
    "Models": ["Accord", "TSX"],
    "Years": ["2003-2007"]
  },
  "features": [
    "Washable and reusable",
    "Million-mile limited warranty",
    "Increases horsepower"
  ],
  "additionalDetails": {
    "Warranty": "Million Mile Limited Warranty",
    "Country of Origin": "USA"
  },
  "sources": [
    "https://www.knfilters.com/...",
    "https://www.amazon.com/..."
  ]
}

Deep Research Response (additional fields):

{
  "...": "...standard fields...",
  "compatibility": {
    "vehicles": ["2003-2007 Honda Accord", "2004-2008 Acura TSX"],
    "engines": ["2.4L I4", "3.0L V6"],
    "trims": ["All trims"],
    "position": "Engine air intake",
    "notes": "Direct replacement for OEM filter"
  },
  "marketing": {
    "shortDescription": "High-flow washable air filter for Honda/Acura vehicles",
    "longDescription": "The K&N 33-2304 is a high-performance...",
    "bulletPoints": [
      "Increases horsepower and acceleration",
      "Washable and reusable - saves money",
      "Million-mile limited warranty"
    ],
    "benefits": [
      "Better engine performance",
      "Long-term cost savings",
      "Environmentally friendly"
    ]
  },
  "crossReferences": {
    "oem": ["17220-RAA-A01", "17220-RBB-505"],
    "alternates": ["Fram CA9360", "Wix 46902"],
    "supersession": {
      "replaces": ["33-2047"],
      "replacedBy": []
    },
    "upc": "024844093042"
  }
}

License

This project is licensed under the MIT License.

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Developer

Peyton Nowlin

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Built with ⚡ by leveraging AI for smarter automotive research