An MCP server that fetches web pages and extracts clean, AI-usable context from them, enabling tools for link discovery, content search, and integrated fetch-and-search operations.
A powerful Model Context Protocol (MCP) server for scraping Behance.net. Extract projects, user profiles, images, and job listings from Behance's creative community without any API keys or subscriptions.
A Context-as-a-Service MCP server that maintains structured, graph-based context for Shopify apps by extracting and summarizing data from web sources and help centers. It enables multi-agent systems to retrieve isolated, provenance-backed context slices or starter bundles via push and pull mechanisms.
This project is a Model Context Protocol (MCP) server that fetches articles from GeekNews. It is implemented in Python, and performs web scraping using BeautifulSoup.
Enables web content extraction and Google Search through Google AI Studio's URL context functionality. Supports batch processing of multiple URLs and returns structured JSON output for web page text and image analysis.
A Model Context Protocol server that enables LLMs to perform Google searches via the Serper API, allowing models to retrieve current information from the web.
A Cloudflare Workers-based server that extracts clean, formatted text from web pages using WebforAI and makes it accessible to AI models through the Model Context Protocol.
Provides instructions and code to set up an MCP server using FastMCP, enabling tool creation for LLM interaction, with an example project for extracting product information from Amazon links.
A Model Context Protocol (MCP) server that provides web search capabilities through DuckDuckGo, with additional features for content fetching and parsing.