"How to create, read from, and write to a database" matching MCP servers:

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

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.

MCP server that converts web page URLs to Markdown via the Zyla API.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

MCP server that fetches remote or local HTML resources and converts them to Markdown, enabling AI clients to summarize or process web content.

An MCP server that automates converting diverse content sources like WeChat articles, YouTube videos, and various document formats into AI-generated outputs such as podcasts and slide decks via Google NotebookLM. It integrates specialized tools for web scraping, OCR, and file transformation to facilitate seamless content generation through natural language.

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

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 X (Twitter) posts into JSON, PDF, PNG, Markdown, or Slack/Discord messages using public endpoints, no API key or login required.

Enables agents to discover how a website serves its data, verify sources with evidence, export OpenAPI 3.1, and generate tested TypeScript or Python clients.

Enables resolving the likely employer behind Gmail, Outlook, iCloud, Yahoo, and other free-mail signups by checking public Gravatar profiles, signed GitHub commits, and LinkedIn results. It returns the person’s name, employer, employer domain, confidence score, and evidence URLs.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Enables AI coding agents to audit websites for PHP runtime vulnerabilities, compile a live Zero-PHP Next.js App Router replacement preview from a WordPress/PHP site, and retrieve remediation guidance.

Enables agents to retrieve the contents of public social media posts — text, author, date, engagement counts, links, photos, and video frames — from X, Instagram, Threads, Facebook, LinkedIn, Bluesky, Mastodon, YouTube, Vimeo, Tumblr, Pinterest, and Reddit by simply passing a post URL. It works entirely without logins, cookies, or API keys, reading only what each site already exposes publicly.

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.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Fetches webpages and converts them into clean Markdown for token-efficient scraping by AI agents, preserving links and supporting configurable multi-page crawling, caching, and robots.txt-aware rate limiting.

Enables AI agents to fetch and crawl web pages, strip noise, and convert content into clean Markdown with preserved links for token-efficient scraping and downstream processing.

Enables AI agents and MCP clients to fetch webpages and crawl sites, converting them into clean, token-efficient Markdown with preserved links, caching, and polite crawling.

Enables AI agents to fetch webpages locally, extract main content, and convert it into clean, token-efficient Markdown with preserved links. Supports configurable multi-page crawling, caching, robots.txt compliance, and optional chunking for downstream processing.

Enables AI agents and MCP clients to fetch web pages and crawl sites locally, converting content into clean Markdown with preserved links, caching, robots.txt compliance, and minimal token usage.

Enables AI agents and LLM pipelines to fetch and crawl web pages, extract readable content, and convert it into clean Markdown with preserved links while minimizing token usage.

Fetches web pages, strips noise, and converts them to clean Markdown with preserved links and optional multi-page crawling, enabling token-efficient web content extraction for AI agents and LLM pipelines.

Enables AI agents and LLM pipelines to fetch and crawl webpages, strip extraneous content, and convert them into clean, link-preserving Markdown for fast, token-efficient scraping.

Enables AI agents to fetch and crawl websites locally, extract main content, preserve links, and convert pages to clean Markdown with minimal token footprint.

Enables AI agents and MCP clients to fetch web pages or crawl sites and convert them into clean, token-efficient Markdown while preserving links.

Fetches webpages and converts them into clean, token-efficient Markdown, optionally crawling multiple linked pages while respecting robots.txt and caching results for AI agents and LLM pipelines.

Enables AI agents and LLM pipelines to fetch and crawl websites locally, strip noise, and convert pages into clean Markdown with preserved links and low token usage.

Enables MCP clients and AI agents to fetch webpages, remove boilerplate, and convert content into clean Markdown with low token usage, optionally crawling multiple pages and preserving links.