"Up-to-date information about Godot documentation" matching MCP servers:

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

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.

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.

This server crawls documentation sites and provides search and page-retrieval tools through MCP, enabling users to query indexed documentation content.

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.

Toolset that crawls websites, generates Markdown documentation, and makes that documentation searchable via a Model Context Protocol (MCP) server for integration with tools like Cursor.

Enables web searches using TAVILY API with fallback to DuckDuckGo, datetime queries, and optional Ollama AI processing. Features HTTP transport with OAuth2 authentication for secure access to search capabilities.

Scrapes and indexes documentation websites to provide AI assistants with searchable access to documentation content, API references, and code examples through configurable URL crawling.

Self-hosted MCP toolkit providing web search, Wikipedia, and arXiv access without mandatory API keys, delivered as a Docker Compose bundle.

Enables intelligent navigation and extraction of documentation from websites, allowing Amazon Q to automatically discover relevant pages, extract clean content, and retrieve code examples from web documentation.

Enables users to retrieve and structure shipment tracking information from DB Schenker's website using natural language queries.

Provides an LLM client with self-hosted web scraping capabilities including scraping, crawling, mapping, searching, structured data extraction, browser interaction, and deep research, without reliance on paid proxy or CAPTCHA services.

Enables LLMs to scrape, index, and search modern and legacy Salesforce documentation by piercing complex Shadow DOM and iframe structures. It supports hierarchical spidering of entire guides and local RAG capabilities using a SQLite database for offline querying.

Extracts and stores documentation content from Microsoft Learn and GitHub URLs into PocketBase with full-text search, metadata preservation, and automatic collection management for easy retrieval and organization.