"How to scrape websites and format content in GitHub Markdown" matching MCP servers:

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.

Converts Markdown files to Atlassian Document Format and publishes them to Confluence, with support for rendering Mermaid diagrams as PNG attachments.

Enables converting any webpage to clean LLM-ready markdown, with extraction, article, and news modes, using a real browser with anti-bot handling.

An MCP server that converts Markdown to HTML, supporting both stdio and HTTP interfaces for easy integration with Cursor and other MCP clients.

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 enables users to download webpages as markdown files using r.jina.ai service, with features for configurable download directories and automatic date-stamped filenames.

Enables converting any URL or website into clean, LLM-ready Markdown, supporting single-page scraping and full-site crawling for AI agents.

Enables AI agents to analyze a piece of content across 11 dimensions and receive ranked, scored recommendations among six cross-media output formats (PPT, infographic, comic, short video script, newsletter, reusable skill), then generate dispatch prompts for the chosen format. It also exposes the format catalog and profile schema as read-only tools, supporting batch routing of an entire content library.

Enables AI to search, retrieve, list notes, and get backlinks from a published Markdown vault (Obsidian) via GitHub Pages.

Converts raw HTML to clean Markdown, optimized for LLM token efficiency and deterministic processing.

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

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.

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.

Enables an Alexa+ host to place and manage customer-care calls by building a case, navigating phone menus, waiting on hold, explaining the issue, guarding sensitive disclosures, handing off identity checks, recording ticket numbers and promises, and scheduling follow-ups.

Automatically transforms markdown templates (like GitHub Issue templates) into MCP tools and FastAPI endpoints. Load templates from local files, directories, or URLs to create typed API endpoints with Swagger UI documentation.

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).

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 39 tools to manage GitHub repositories, branches, issues, PRs, workflows, and more via the GitHub CLI, enabling natural language interaction with GitHub.

Persistent memory and pattern learning for AI coding assistants via MCP.

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.

A multi-server system that converts PDF documents to Markdown format using FastMCP architecture with upload and convert servers orchestrated by a reactive client agent.

Crawl entire websites, sitemaps, and documentation portals into clean, LLM-ready Markdown without ads, cookie popups, or noise for RAG pipelines and AI agents.

Real-time Amazon Sponsored Products (SP) ad placements, keyword tracking, and comprehensive review data for AI Agents. Enables LLMs to autonomously conduct competitor ad audits, consumer sentiment analysis (VOC), and product optimization.

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.

Enables AI assistants to convert CSS-animated SVGs into videos (MP4/WebM/MKV/MOV) and animated images (aPNG/GIF) with frame-accurate rendering and transparency support.

Enables AI agents to inspect any public domain’s web technology stack, email deliverability and DNS health (MX, SPF, DKIM, DMARC, MTA-STS, TLS-RPT, BIMI), and HTTPS security posture with typed JSON scores and remediation-ready findings, plus history, bulk checks, monitoring alerts, and reverse technology lookups.

Enables reading and verifying C2PA Content Credentials from images and videos through both embedded manifests and invisible watermarks. Supports direct filesystem access, URL checking, and provides structured provenance data including creator identity, AI generation info, and content authenticity.

Enables AI agents to extract clean, structured web content (articles, tables, links, visual layouts) optimized for LLM token efficiency, with fast response times and optional JavaScript support.