Projects sharing features with Upton

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

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

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

RubyRetriever (http://softwarebyjoe.com/rubyretriever/)

Ruby gem for web scraping purposes. It scrapes a given URL, and returns you its title, meta description, meta keywords, links, images...

Nokogiri is an XML and HTML parsing library that builds navigable document trees from strings, files, or URLs using native C parsers for speed and standards compliance. It provides a CSS selector engine that translates CSS3 selectors into XPath expressions for querying nodes, an XPath query interface with namespace support, a document manipulation toolkit for modifying parsed documents, XSD schema validation, and XSLT transformation capabilities. The library wraps libxml2 and libxslt C libraries with Ruby bindings for high-performance parsing, and integrates Google's Gumbo parser for standard

Web crawler with very flexible crawling options. Can either use standalone or can be used with resque to perform clustered crawls.

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.