15+ Best Open Source Web Crawlers for LLM & AI
Recent advancements in Generative AI are moving modern crawlers beyond raw HTML. Agentic web crawlers now use natural-language prompts to select links, rather than relying on fixed rules. These tools produce token-efficient markdown, making them essential for high-performance RAG pipelines.
Compare the top open-source web crawlers, based on their architecture, programming language, and capability to handle the JavaScript-heavy web:
Top 15+ open-source web crawlers and web scrapers
1. Crawl4AI
Crawl4AI is an open-source Python library optimized for RAG (Retrieval-Augmented Generation) and LLM pipelines. The “Stability & Recovery” update introduced a crash recovery system that lets large-scale crawls resume from checkpoints with an on_state_change callback, preventing data loss during hardware or network interruptions. The new “Prefetch Mode” significantly accelerates URL discovery over traditional methods.
Advantages of Crawl4AI:
- Features a “Prefetch Mode” that identifies and queues URLs faster than previous versions.
- Protects long-running crawl jobs by allowing users to resume progress from the last successful state change.
- Provide structured data that integrates with vector databases and AI frameworks.
2. Firecrawl
Firecrawl handles the complexities of sitemap crawling, JavaScript rendering, and content cleaning. As of January 2026, Firecrawl has transitioned into an “agentic” data layer with the launch of “Parallel Agents.”
This allows the platform to process thousands of concurrent research queries simultaneously. The introduction of the Firecrawl CLI and “Skills” enables AI agents (such as Claude Code) to natively access web data through a simplified file-based context management system.
Advantages of Firecrawl:
- Supports batch processing of thousands of agentic research queries at once.
- Automatically identifies and crawls all subpages of a domain without requiring manual URL lists.
3. Crawlee
Crawlee is an open-source Node.js library for scraping and browser automation, created by Apify. Crawlee has three crawler classes: CheerioCrawler, PuppeteerCrawler, and PlaywrightCrawler (browser-based crawlers).
CheerioCrawler is an HTTP crawler with HTML parsing and no JavaScript rendering, making it ideal for static content. PuppeteerCrawler / PlaywrightCrawler is ideal for JS-heavy pages with automatic browser management.
Advantages of Crawlee:
- Includes anti-blocking tools out of the box, such as auto-generated human-like headers and TLS fingerprints, proxy rotation, and session management.
- Offers a type-hinted API that supports both HTTP and browser-based crawlers.
4. Apache Nutch
Apache Nutch is developed in Java by the Apache Software Foundation for both enterprise and research-scale crawling. Nutch excels at batch processing and distributed crawling via Hadoop MapReduce.
Advantages of Apache Nutch:
- Leverages Apache Hadoop’s MapReduce framework for crawling and processing data at scale.
- Built on a modular plugin system (e.g., Tika for parsing, Solr/Elasticsearch for indexing).
- Handles a wide array of content types (HTML, XML, PDFs, Office formats, and RSS feeds).
5. BUbiNG
BUbiNG is a high-throughput, fully distributed crawling system developed by the Laboratory in Java. The tool is extensively customizable via configuration files and supports reflection-based components. It informs users about tailored filters, data flow, and crawl logic.
Advantages of BUbiNG:
- Crawling speed scales linearly with the number of agents; a single agent can crawl thousands of pages per second.
- Enforces customizable delays both per host and per IP.
6. Heritrix
Heritrix is an archival-quality web crawler written in Java, primarily used for web archiving. It returns site snapshots in standardized formats, such as ARC and its successor, preserving both HTTP headers and full responses in large, grouped files.
Advantages of Heritrix:
- Offers both a web-based UI and a command-line interface, allowing flexible management of crawl jobs and schedules.
- Supports components for fetching, parsing, scoping, and politeness rules.
7. JSpider
JSpider is a Java-powered web spider that offers a plugin-oriented design. You can add functionalities such as dead link detection, performance testing, and sitemap creation. It can be run via the command line or invoked as a library in Java applications.
Advantages of JSpider:
- Supports custom plugin development
- Offers a user manual in PDF format, covering installation, configuration, usage, and extension development.
8. Node Crawler
Node Crawler is a widely adopted library for building web crawlers in Node.js. Node Crawler uses Cheerio by default for server-side parsing.
Advantages of Node Crawler:
- Supports configurable concurrency, retries, rate limiting, and a priority-based request queue.
- Includes built-in charset detection, UTF-8 by default, automatic conversion, and retry logic for resilience.
9. Nokogiri
Nokogiri is an HTML and XML parsing library in the Ruby ecosystem that combines the performance of native C-based parsers with a user-friendly API. The system offers multiple parsing modes:
- DOM parser for in-memory document handling
- SAX (streaming) parser for large documents
- Builder DSL to generate XML/HTML programmatically, plus XSLT and XML schema validation support.
Advantages of Nokogiri:
- Includes precompiled native libraries for easy installation, eliminating manual dependencies.
- Supports document traversal and querying using both CSS3 selectors and XPath 1.0 expressions.
- Handles malformed markup, supports streaming (SAX), and lets users build XML/HTML via a DSL.
10. Norconex HTTP Collector
Norconex HTTP Collector, or Norconex Web Crawler, is a Java-based, open-source enterprise crawler. Norconex employs a two-tier design in which a Collector orchestrates execution by delegating crawling tasks to one or more Crawler instances.
Advantages of Norconex HTTP Collector:
- Supports full and incremental crawls, adaptive scheduling, and hit intervals customized per schedule.
- Offers content extraction across various formats (HTML, PDF, Office, images), along with language detection, metadata extraction, and the capture of featured images.
- Supports advanced content manipulation, including deduplication, URL normalization, sitemap parsing, canonical handling, external scripting, and dynamic title generation.
11. OpenSearchServer
OpenSearchServer is an open-source search engine framework built on Lucene. Its integrated web-crawling capabilities make it especially well-suited for applications that combine crawling, indexing, and full-text search.
Advantages of OpenSearchServer:
- Supports HTTP/HTTPS crawling for web pages. It allows URL parameter filtering, crawl session settings, and a URL browser UI for checking link status.
- Crawls local and remote file systems (NFS, CIFS, FTP, FTPS) to capture attributes for indexing.
- Offers built-in parsers that extract data and metadata from formats such as HTML/XHTML.
- Supports multilingual indexing (up to 18 languages).
12. Porita
Portia is a browser-based tool that enables users to create web scrapers without writing a single line of code. It’s designed to allow visual data extraction through intuitive page annotations. Portia can also be deployed via Docker or Vagrant for self-hosting.
Advantages of Porita:
- When you annotate a sample page by clicking on elements you want to collect. The tool learns the structure and automatically applies it to similar pages.
- Stops crawling if fewer than 200 items are scraped within an hour by default to prevent endless loops.
- Configures login requirements or enables JavaScript rendering with Splash.
13. PySpider
PySpider is a Python-based web crawling framework that provides a browser-based interface, including a script editor, task monitor, project manager, and results viewer. Users can schedule periodic crawls, prioritize tasks, and re-crawl based on content age.
Advantages of PySpider:
- Can handle dynamic content loading and user interactions.
- Divides the crawl process into modular components like “Scheduler, Fetcher, Processor, Monitor, and Result Worker”.
14. Scrapy
Scrapy is an open-source Python framework used for web data extraction and web crawling. With the release of Scrapy 2.14.1, the framework fully adopted native async/await standards.
The tool provides a Selector API wrapping lxml for parsing HTML/XML. Both can be mixed in one spider.
While older versions required complex setups, Scrapy now features integration with Playwright, making integrated JavaScript rendering the modern standard for the framework.
Advantages of Scrapy:
- Fetches web content using asynchronous HTTP.
- Modify requests/responses before they reach spiders or after they are downloaded.
- Queues requests and decides which one to process next.
15. StormCrawler
StormCrawler is an open-source SDK for building distributed web crawlers in Java. Instead of the request–response loop, StormCrawler uses Storm topologies (directed acyclic graphs (DAGs) of processing components). The tool enables users to swap or customize URL sources, parsers, and storage. It requires knowledge of Java and Apache Storm.
Advantages of StormCrawler:
- Offers regex-based or custom filters to control which URLs to crawl.
- Support for HTTPS, cookies, and compression.
- Fetches and processes pages continuously, rather than in batch jobs.
- Tracks crawl progress and schedules recrawls.
16. Web Harvest
Web-Harvest is considered a legacy tool. The last official version, v1.0, was released in 2007. It does not support modern dynamic web standards, so it is best for historical research or simple XML-based tasks.
Web Harvest is configured using XML files. Users can define the data collection logic by specifying a sequence of processors and actions in an XML file.
The tool heavily relies on technologies such as XPath, XSLT, and Regular Expressions to extract all the data from HTML and XML documents.
Advantages of Web Harvest:
- Allows embedding scripting languages such as Groovy and BeanShell in its XML configurations.
- Has control-flow constructs, such as loops, to iterate over a list of items on a page.
17. WebSphinx
WebSphinx (also written as SPHINX) is a Java-based web crawler toolkit. Users can develop, run, and visualize crawls, often without writing any code for simple tasks. It doesn’t render JavaScript, as it is designed for a simpler and static web.
Advantages of WebSphinx:
- Includes a graphical user interface (GUI) called the “Crawler Workbench” that could run in a web browser as a Java applet.
- Offers components called “classifiers” that could be attached to a crawler to analyze and label pages and links with useful attributes.
What are open source web crawlers?
Open-source web crawlers are software programs that automatically crawl the internet and extract data. They are used for indexing websites for search engines, web archiving, SEO monitoring, and data mining.
Developers can modify the source code for specific needs. For example, you can change how they discover web pages, what data they extract, and how they store it.
FAQs about open-source web crawlers
To choose the right open source crawler for your business or scientific purposes, make sure to follow best practices:
Participate in the community: Open-source crawlers typically have large, active communities where users share new code and bug fixes. Businesses can engage with the community to quickly find solutions to their problems and discover effective crawling methods.
Update open-source crawlers regularly: Businesses should track open-source software updates and deploy them to patch security vulnerabilities and add new features.
Choose an extensible crawler: It is important to select an open-source crawler that can handle new data formats and fetch protocols used to request access to pages. It is also crucial to choose a tool that can run on the devices used in the organization (Mac, Windows, etc.).
Depending on the frequency and scale of your web crawling needs, you may find programming your web crawler more productive in the long run. In-house web crawlers will likely need technical maintenance.
Therefore, if you do not have technical resources built into your team and will outsource the web crawling effort, using an open source tool or working with web scrapers may be less hassle-free, given that you would be dependent on a technical freelancer for the in-house solution as well.
Open-source crawlers are legal to use. Legality depends on factors such as compliance with website terms of service, respecting robots.txt, or ethical crawling.
Open-source crawlers are built in a variety of programming languages, including (e.g., Apache Nutch, Heritrix, BUbiNG), JavaScript/Node.js (Crawlee or Node Crawler), Ruby (Nokogiri), and Python library (Scrapy, BeautifulSoup, and PySpider).
Yes, but not all of them. Static crawlers only fetch raw HTML and can’t capture content rendered by JavaScript. Crawlers with JavaScript rendering support, such as headless browsers, web automation frameworks, and rendering services.
Yes. Common cloud deployment options include Docker containers, Serverless Functions, and managed services.
Running crawlers in the cloud enables them to operate 24/7 without requiring your own machine to be on.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE and NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and resources that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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