"Methods to Scrape a Website and Fetch Markdown Files from GitHub" matching MCP servers:

Enables structured extraction of methods and reproducibility heuristics from academic papers, allowing AI agents to obtain metadata, full text, structured methods, code repository discovery, and a no-clone reproducibility verdict from a paper URL.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.

Fetch URLs and return clean, LLM-ready markdown with metadata and layered prompt injection defense. Configurable timeouts, word limits, JS rendering, and link extraction. All-in-one MCP server + CLI.

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

A lightweight MCP server for basic file operations, enabling reading, writing, and listing files securely via the Model Context Protocol.

A comprehensive web scraping server that transforms web content into clean, agent-ready Markdown with automatic citations and efficient caching. It features a robust suite of tools for metadata extraction, sentiment analysis, SEO auditing, and security scanning while strictly adhering to robots.txt policies.

Write your resume in Markdown and export to PDF with AI assistance, using a built-in stylesheet and tools for conversion.

A web-fetch MCP server for LLM agents that fetches pages with an escalation ladder through different engines, raising FetchBlocked instead of returning blocked content.

Model Context Protocol server for fetching web content and processing images. This allows Claude Desktop (or any MCP client) to fetch web content and handle images appropriately.

Provides tools to fetch web content in HTML, JSON, text, or Markdown formats via MCP. Supports custom headers, length limits, and start index.

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

A generic Markdown vault MCP server with FTS5 full-text search, semantic vector search, frontmatter-aware indexing, incremental reindexing, and non-markdown attachment support that exposes search, read, write, and edit tools.

A Model Context Protocol (MCP) server that provides a local-first RAG engine for your markdown documents. It uses a file-based Milvus vector database to index your notes, enabling LLMs to perform semantic search and retrieve relevant content from your local files.

MCP server that turns DOI, URL, or paper titles into structured Markdown full-text with metadata and assets, enabling AI agents to read beyond abstracts.

Reduces token consumption by 73-87% by cleaning web and API data before it reaches the LLM context window. Supports fetching URLs, searching the web, optimizing JSON, and more.

A dedicated web content fetching and conversion MCP server that provides tools for fetching, converting, and extracting data from web pages.

Enables scraping of emails, phone numbers, and social profile links from website domains. Supports batch processing of up to 20 domains and can find company websites by keyword/company name.

Headless semantic MCP server for Obsidian, Logseq, Dendron, Foam, and any markdown folder. Features built-in hybrid semantic search, surgical AST editing, template scaffolding, zero-config local embeddings, and workflow tracking.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

An MCP server that connects Claude to your real GitHub activity and tells you what to build and ship publicly to make your resume credible.