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This project is a Model Context Protocol server that connects large language models to web scraping and crawling tools. It functions as a bridge, allowing LLM clients to utilize a web crawling engine and scraping utilities to extract and process web data. The server integrates a markdown web converter that transforms dynamic web pages and PDF documents into clean markdown to optimize consumption by AI models. It also provides a browser automation interface for controlling headless sessions and bypassing access restrictions. The system covers broad capabilities including large-scale website d
This project is a comprehensive resource directory for web data extraction, providing a curated collection of tools and libraries for parsing data, automating browsers, and managing network operations. It serves as a guide for extracting structured information from HTML, XML, JSON, and PDF formats. The toolkit focuses on advanced data collection strategies, including headless browser automation to interact with JavaScript and a suite of network utilities for DNS resolution and WebSocket connections. It specifically covers methods for bypassing bot protections through proxy pool management, us
Firecrawl MCP Server is a Model Context Protocol tool server that exposes the full suite of Firecrawl’s web scraping, crawling, and automation capabilities as tools that large language models can invoke directly. It acts as a proxy to the Firecrawl cloud platform, which manages headless browser orchestration, async job queues, and rate limiting behind the scenes. The server distinguishes itself by packaging autonomous web agents — both a research agent that browses and collects structured data from multiple pages, and a general web agent that performs multi-step browsing and extraction tasks
Omniparse is a multimodal content parser and generative AI ingestion engine designed to convert documents, images, and multimedia into a uniform format. It functions as a data preprocessing pipeline that transforms diverse raw data sources into structured markdown to improve the performance of large language model workflows. The system extracts text and structural data from PDFs, images, audio, and video files. It includes a web crawler that converts dynamic website content into clean markdown and a multimodal transformation process that maps disparate input formats into a unified data schema
Write web scrapers in Ruby using a clean, AI-assisted DSL. Kimurai uses AI to figure out where the data lives, then caches the selectors and scrapes with pure Ruby. Get the intelligence of an LLM without the per-request latency or token costs.
The main features of vifreefly/kimuraframework are: Web Crawling.
Projects with overlapping indexed features include: mendableai/firecrawl-mcp-server — This project is a Model Context Protocol server that connects large language models to web scraping and crawling… lorien/web-scraping — This project is a comprehensive resource directory for web data extraction, providing a curated collection of tools… adithya-s-k/omniparse — Omniparse is a multimodal content parser and generative AI ingestion engine designed to convert documents, images, and… firecrawl/firecrawl-mcp-server — Firecrawl MCP Server is a Model Context Protocol tool server that exposes the full suite of Firecrawl’s web scraping,… jaimeiniesta/metainspector — Ruby gem for web scraping purposes. It scrapes a given URL, and returns you its title, meta description, meta… felipecsl/wombat — Lightweight Ruby web crawler/scraper with an elegant DSL which extracts structured data from pages.