watercrawl/WaterCrawl

Transform Web Content into LLM-Ready Data

What it solves

WaterCrawl provides a scalable way to crawl web pages and extract relevant data from the internet. It simplifies the process of gathering large amounts of web content while offering tools to target specific content, manage crawl depth, and integrate the resulting data into AI and automation workflows.

How it works

Built with Python, Django, Scrapy, and Celery, the system operates as a self-hosted web application. It uses asynchronous processing to handle crawls and searches in real-time, providing progress updates via Server-Sent Events (SSE). It exposes a REST API with OpenAPI documentation and provides SDKs for multiple languages (Python, Node.js, Go, and PHP) to allow programmatic access to the extracted data.

Who it’s for

It is designed for developers and data engineers who need to automate web data extraction and feed that information into other systems, particularly those building AI agents or automation pipelines.

Highlights

  • Customizable Crawling: Control over depth, speed, and content targeting.
  • AI Integrations: Native plugins and integrations for Dify, N8N, and OpenAI.
  • Multi-language Support: Ability to search and crawl content across different languages and countries.
  • Developer-friendly: Includes a comprehensive REST API and multiple client SDKs.
  • Self-hosted: Open-source deployment options for full data control.

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