An MCP server that gives AI agents direct access to VMware vSphere infrastructure, enabling VM lifecycle management, snapshots, datastore operations, networking, and more via 55 typed tools built on govc.
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.
An MCP server that exposes the llms.txt file and its referenced local or external resources from a project root to provide context for AI models. It automatically parses documentation links and URLs to make them accessible as additional MCP resources.
Enables auditing any website for AI-answer readiness, returning a score and actionable fix list based on llms.txt, schema, sitemap, and related checks.
Enables AI agents to read any web page as clean Markdown and inspect its metadata, structure and technology stack, plus check redirects, TLS certificates, security headers, robots.txt, sitemaps, feeds, domains, SEO, broken links, email authentication (SPF/DMARC/DKIM) and SSO (SAML/OIDC). It also provides developer utilities such as cron, regex, color, Unicode and time-zone tools along with Hyperliquid perpetuals market data, all hosted remotely on Apify with pay-per-call pricing.
MCP server that gives AI agents access to current web information through web_search and fetch_url tools, using Tavily, Brave, and DuckDuckGo providers with automatic fallback.
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.
Enables processing, validation, optimization, and analysis of 3D models with glTF/GLB support, including format conversion, compression (Meshopt/Draco), texture optimization, and detailed model statistics.
Enables fast, token-efficient access to large documentation files in llms.txt format through semantic search. Solves token limit issues by searching first and retrieving only relevant sections instead of dumping entire documentation.
Enables agents to discover the llms.txt index covering any site, fetch its linked documentation pages as markdown, and search across parsed indexes by section heading, link title, and notes.
A generic MCP (Model Context Protocol) server for any Hugo blog, deployed on Cloudflare Workers. It reads your blog's llms.txt and llms-full.txt files and exposes them as structured tools that AI assistants can query to understand your content.
AutomateLab Content Distribution publishes content across DEV.to, Hashnode, GitHub Discussions, Reddit and Bluesky, with browser workflows for LinkedIn, Medium and X. Tracks publishing state and adapts content per platform. Product and documentation: https://automatelab.tech/products/mcp/content-distribution-mcp/
Provides AI agents with structured short-form content mechanics including hooks, script structures, retention strategies, and CTAs, along with auditing tools to avoid common posting failures.
Enables interaction with Prismic through tools for reading documents, managing media assets, and performing content migrations or updates. Supports the Prismic Content, Asset, Migration, and Custom Types APIs with secure write operations and multi-transport support.