"How to scrape content from a website" matching MCP servers:

MCP server that fetches and converts website pages into clean markdown for agents, with sitemap-based discovery, disk caching, and polite crawling (robots.txt, rate limiting).

Enables converting webpages into structured JSON using CSS-selector schemas, with anti-bot handling and support for protected pages.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Extract content from URLs, documents, videos, and audio files using intelligent auto-engine selection. Supports web pages, PDFs, Word docs, YouTube transcripts, and more with structured JSON responses.

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

Enables deterministic bilingual website intelligence audits by URL, returning fixed English or Spanish findings without ever contacting the submitted site.

Fast, token-efficient web content extraction tool that converts websites to clean Markdown for AI agents, featuring smart caching, content extraction with Mozilla Readability, and polite crawling capabilities.

Multi-platform content distribution — draft posts, repurpose content, generate carousels, schedule, analyze performance, create threads. 7 MCP tools.

An MCP server that uses AI to generate structured Asana project plans from diverse sources like text, PDFs, and meeting transcripts. It enables users to preview, generate, and directly sync detailed task lists, subtasks, and dependencies into Asana.

Lets AI assistants manage a self-hosted content hub: create, edit, publish, and update articles across nine platforms, refresh account article lists, and sync changes through natural language.

MCP server that fetches raw HTML content from a given URL to provide web context to LLMs.

A specialized Model Context Protocol server that enhances AI-assisted medical learning by connecting Claude Desktop to PubMed, NCBI Bookshelf, and user documents for searching, retrieving, and analyzing medical education content.

Provides SEO audits, content analysis, and domain overviews through an MCP server, including on-page, technical, and authority metrics with built-in browser rendering and anti-bot handling.

Enables tracking webpage content and price changes over time, including diffs, historical records, and alerts. Supports protected pages with automated browser rendering and anti-bot handling.

MCP server exposing content contract validators (SEO.md, PRODUCTHUNT.md, LINKEDIN.md) as tools so AI agents can verify generated content against concrete rules without maintaining linters. It provides linting and JSON-LD export tools with config and content passed as parameters, not file paths.

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 enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Enables AI agents to scrape, crawl, clean, chunk, and index website content into Azure AI Search for full-text retrieval.