"Resources for Learning Web Scraping" matching MCP servers:

Enables AI assistants to fetch public web pages as readable text or HTML, with caching, live refresh, and parallel job handling.

Enables fetching any public web page through managed proxies, with optional JavaScript rendering, returning markdown, text, HTML, or structured JSON.

Evidence-governed coding agent memory and knowledge lifecycle MCP server for DeepSeek Harness (DSH), OpenAI Codex, and Google Antigravity. Provides local SQLite FTS5 + semantic hybrid retrieval, automatic session/compaction checkpointing, counter-example demotion, and a hard 1,200-char context budget guardrail with zero third-party Python dependencies.

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

Enables reading and sending messages in Google Messages for web through a paired Chrome tab using chromefile, with tools for status, listing conversations, reading message history, and sending texts.

Enables developers to record feature-based development processes and turn Git changes, AI conversations, token usage, technical decisions, and debugging attempts into structured Obsidian learning reviews.

Enables AI agents to index, search, and validate lessons learned across project repositories via a local SQLite index, providing learning-loop resources and verified-solution tracking without loading full files into conversations.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

Turns your PDFs into locally stored flashcards and quizzes, grades your answers, and schedules spaced-repetition reviews entirely on your machine.

Provides educational tools for developers to learn programming concepts, review code, get best practices, compare approaches, generate learning paths, debug, explain code, and quiz themselves.

Provides current weather data for any city using the Open-Meteo API, exposed as an MCP tool for integration with MCP clients.

A beginner-friendly MCP server built in plain Node.js/JavaScript that exposes five tools (calculator, UUID generator, read notes, get weather, password generator) to teach how the Model Context Protocol works under the hood.

Enables educational and learning tasks including flashcard generation with Anki integration, Zotero library management, Obsidian vault interaction, and mathematical expression verification with LaTeX support.

A comprehensive tutorial project that teaches Model Context Protocol (MCP) development from beginner to advanced levels, covering both server-side and client-side development.

A local MCP server that helps you maintain a personal Japanese learning knowledge base, including vocabulary, confusion relations, mistakes, and spaced-repetition reviews. It provides tools and prompts for managing and reviewing your Japanese learning data without calling external LLM APIs.

Enables an AI assistant to author sentence-synced, motion-graphics lessons: it writes and validates lesson JSON, runs example code to verify output, renders 3D illustrations with Blender hotspots, synthesizes multi-voice narration with timing data, and builds a single-file HTML textbook. Supports any subject, from math and science to English and programming.

A sovereign, AI-driven pedagogical and spaced-repetition skills development MCP server supporting progressive syllabi, Bloom's Taxonomy, and secure LMS handshakes.

Enables AI agents to extract clean LLM-ready markdown and readable articles from web pages, parse metadata, tables, links, feeds, and contact info, audit paywalls, SEO, and XSS, and access these tools via Streamable HTTP or a stdio bridge.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

Enables web search and web fetch operations using Ollama's hosted APIs, allowing MCP clients to search the web and retrieve page content.

Odysseus Web MCP is a standalone Model Context Protocol (MCP) server for safe public-web search and URL fetching.

MCP server that lets AI editors execute JavaScript, read console output, and simulate clicks/input on static web pages. Supports multiple browser pages and can be deployed remotely via HTTP transport.

MCP server for web page fetching (converting to Markdown/text with automatic fallback between Tavily and Firecrawl) and web search via Tavily.

Educational MCP server with 17 tools for mathematical calculations, matrix operations, statistical analysis, and data visualization. Includes persistent workspace, cloud hosting, and safety features like restricted eval.

MCP server providing free, IP-direct tools for web search, crawling, anti-detect browsing, and structured data from Wikipedia, Wikidata, GitHub, and YouTube.

A portable MCP server that scrapes SPA/JS-rendered webpages and extracts structured API endpoint data. It uses headless Chromium to render JavaScript and provides tools for scraping, endpoint extraction, screenshots, and database seeding.

Provides web search and content extraction tools for AI assistants, with zero configuration and swappable backends.

Enables a locally-run LLM to search the web, fetch pages as markdown, make arbitrary HTTP requests, and optionally render pages with headless Chromium.

⚡ 87% Token-compressed clean web scraping, YouTube AI transcripts, and PDF extraction for LLMs. Instant Free Trial with zero setup (No wallet/crypto required). Supports gasless agent vaults and EIP-712 on-chain oracle verification on Polygon, Base & Arbitrum.

Gives AI agents local web search and page reading with no API keys, layering a SearXNG-backed search cache with browser-based fallbacks and returning clean page text from HTML, PDF, JSON, and archived snapshots. Fetches run in Docker alongside the search engine with SSRF protection, egress filtering, and untrusted-content marking so agents can safely retrieve live web data.