"Resources for Learning Web Scraping" matching MCP servers:

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.

MCP server that gives AI agents access to current web information through web_search and fetch_url tools, using Tavily, Brave, and DuckDuckGo providers with automatic fallback.

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.

A learning-focused MCP server that demonstrates how to build arithmetic tools for AI assistants, currently featuring addition functionality with structured input/output.

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.

Guides users to official WCAG and W3C resources for learning web accessibility, without providing its own explanations.

A task manager MCP server that demonstrates core MCP concepts (resources, tools, prompts, stdio) and syncs data with a Next.js web app.

AI learning assistant for families. Manages game time rewards based on school grades, homework, and bonus tasks. Syncs with EduPage/PRONOTE. 78 MCP tools with instruction workflows.

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

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.

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.

Enables AI agents to learn from their work by recording tasks, extracting patterns, detecting mistakes, and proactively surfacing insights, all using the agent's own model through a cooperative intelligence pattern.

Extends the official Obsidian MCP server with intelligent learning and second-brain features, including AI-generated challenges, progress analytics, spaced repetition, and knowledge gap analysis.

A spaced-repetition study scheduler that syncs with Obsidian notes and uses SBB commute data to optimize study slots.

This MCP server provides an AI-driven learning and knowledge management platform that automatically summarizes conversations, manages knowledge graphs, tracks project progress, explores new technologies, and generates study plans through specialized agents.

Enables Codex to send text tasks to ChatGPT web, await responses, continue conversations, choose reasoning effort, and manage projects through MCP tools on macOS.

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

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.

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

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.

Provides web access capabilities for LLMs including search, fetching, content extraction, PDF reading, image viewing, and screenshots.

Enables Claude and other LLMs to read and parse web content, with smart fallback strategies to bypass access restrictions (e.g., paywalls, Cloudflare) and output Markdown.

Enables MCP-capable agents to perform local web research under a declared plan with session budgets, user-approved limit extensions, and guardrails for safe searching, page fetching, content extraction, and audit logging.

Enables agents to perform compact, cited web research within caller-set token caps, returning direct answers, short verbatim quotes, numbered sources, and noted gaps.

Enables agents to perform local metasearch, scholarly and code/model lookups, and fetch rendered web pages or PDFs as paginated markdown, including stealth browsing and arXiv paper overviews.