"Comment perdre du poids (How to lose weight)" matching MCP servers:

Enables AI clients to search Xiaohongshu notes by brand and category, batch extract comments, and perform keyword/sentiment/heat analysis, with results exported as Excel and JSON reports.

Enables automated searching and commenting on Xiaohongshu with AI-generated comments via MCP clients like Claude, supporting login persistence, note analysis, and four comment types.

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

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

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.

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.

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

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

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.

Converts any webpage URL to clean, well-formed Markdown with title and H1 preservation, URL validation, and graceful fallbacks. One of 16 single-purpose servers in an open-source monorepo with full CI/CD to PyPI.

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.

Converts WeChat Official Account articles to clean Markdown with locally downloaded images, supporting single and batch operations via MCP tools.

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

Web search, crawling and ranking evaluation on your own YaCy peer: no API key, no central service. Results carry author-signature verdicts and declared tags.

Enables agents to fetch a public web page or WeChat article in one call and receive complete Markdown, locally saved images, JSON metadata, offline HTML, and optional PDF, with paginated continuation when output is truncated.

Enables browser automation over MCP using a real Chrome browser with existing profile, supporting real tabs, downloads, cookies, and RPA workflows.

Scrapes dynamic web pages via headless Chrome, stripping clutter and ads, and returns clean Markdown or JSON content. It integrates with Cloudflare Workflows and monetizes each extraction through the x402 protocol.

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

Enables users to look up any company's Google advertising by domain or verified advertiser name, returning one row per ad with its format, first and last shown dates, creative link, and Transparency Center permalink. Also returns a per-company summary stating whether the advertiser runs Google ads, roughly how many, and in which formats, with unfiltered by region, format, recency, or ad count.

Enables users to search Reddit by keyword or subreddit, read thread URLs with comments, filter and sort results, and receive flat post and comment rows without needing a Reddit login or API key.

Enables capturing recent posts from LinkedIn profiles and company pages, including real reaction and comment counts and publicly visible commenters, without requiring a LinkedIn account, cookies, or credentials.

LinkedIn prospect intelligence inside Claude. It automates the research behind outreach, not the sending: scrapes posts, profiles and comment threads into a local SQLite database, classifies what a person or company actually posts about, mines comment threads for people already describing your problem, and surfaces uncommon commonalities worth opening with.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Exposes three read-only MCP tools that let an assistant check whether specified AI crawlers are allowed by a site's robots.txt and how a URL responds when fetched with each bot's user-agent, fetch a page as a single named bot, and generate a robots.txt that welcomes AI crawlers.