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Scrapecraft

🤖 AI-powered web scraping editor with visual workflow builder. Build, test & deploy web scrapers using natural language. Powered by ScrapeGraphAI & LangGraph.

Install / Use

/learn @ScrapeGraphAI/Scrapecraft

README

ScrapeCraft - AI-Powered Web Scraping Editor

ScrapeCraft is a web-based scraping editor similar to Cursor but specialized for web scraping. It uses AI assistance to help users build scraping pipelines with the ScrapeGraphAI API.

https://github.com/user-attachments/assets/defaf7ad-23da-40b7-82cd-3b2a4d1d22c9

API Banner

Features

  • 🤖 AI-powered assistant using OpenRouter (Kimi-k2 model)
  • 🔗 Multi-URL bulk scraping support
  • 📋 Dynamic schema definition with Pydantic
  • 💻 Python code generation with async support
  • 🚀 Real-time WebSocket streaming
  • 📊 Results visualization (table & JSON views)
  • 🔄 Auto-updating deployment with Watchtower

Tech Stack

  • Backend: FastAPI, LangGraph, ScrapeGraphAI
  • Frontend: React, TypeScript, Tailwind CSS
  • Database: PostgreSQL
  • Cache: Redis
  • Deployment: Docker, Docker Compose, Watchtower

Prerequisites

  • Docker and Docker Compose
  • OpenRouter API key (Get it from OpenRouter)
  • ScrapeGraphAI API key (Get it from ScrapeGraphAI)

Quick Start with Docker

  1. Clone the repository

    git clone https://github.com/ScrapeGraphAI/scrapecraft.git
    cd scrapecraft
    
  2. Set up environment variables

    cp .env.example .env
    

    Edit the .env file and add your API keys:

  3. Start the application with Docker

    docker compose up -d
    
  4. Access the application

    • Frontend: http://localhost:3000
    • API: http://localhost:8000
    • API Docs: http://localhost:8000/docs
  5. Stop the application

    docker compose down
    

Development Mode

If you want to run the application in development mode without Docker:

Backend Development

cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

Frontend Development

cd frontend
npm install
npm start

Usage

  1. Create a Pipeline: Click "New Pipeline" to start
  2. Add URLs: Use the URL Manager to add websites to scrape
  3. Define Schema: Create fields for data extraction
  4. Generate Code: Ask the AI to generate scraping code
  5. Execute: Run the pipeline to scrape data
  6. Export Results: Download as JSON or CSV

Remote Updates

The application includes Watchtower for automatic updates:

  1. Push new Docker images to your registry
  2. Watchtower will automatically detect and update containers
  3. No manual intervention required

API Endpoints

  • POST /api/chat/message - Send message to AI assistant
  • GET /api/pipelines - List all pipelines
  • POST /api/pipelines - Create new pipeline
  • PUT /api/pipelines/{id} - Update pipeline
  • POST /api/pipelines/{id}/run - Execute pipeline
  • WS /ws/{pipeline_id} - WebSocket connection

Environment Variables

| Variable | Description | How to Get | |----------|-------------|------------| | OPENROUTER_API_KEY | Your OpenRouter API key | Get API Key | | SCRAPEGRAPH_API_KEY | Your ScrapeGraphAI API key | Get API Key | | JWT_SECRET | Secret key for JWT tokens | Generate a random string | | DATABASE_URL | PostgreSQL connection string | Auto-configured with Docker | | REDIS_URL | Redis connection string | Auto-configured with Docker |

License

MIT

View on GitHub
GitHub Stars611
CategoryDevelopment
Updated11d ago
Forks96

Languages

Python

Security Score

100/100

Audited on Mar 16, 2026

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