"Information about web scraping or crawling" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Upfling provides a zero-configuration environment for hosting static websites. You can upload individual HTML, CSS, and JS files or drag an entire folder to receive a live website with SSL on a shareable URL in seconds. It eliminates the need for complex setup or server configuration, focusing on rapid deployment for static web projects. You can also upload documents like PDFs and add password protection. All of this can be done using the API or MCPs from AI chat platforms.
AI infrastructure design agent. Describe your app in plain English; Riley designs, prices, and deploys AWS or GCP infrastructure with generated Terraform.
Ask your AI assistant a cost question. Get allocation, correlation, and explanation in one response. Costory connects Claude, Codex, or Cursor to normalized cost data across AWS, GCP, Azure, Datadog, OpenAI, and Anthropic. https://costory.io Free trial 14 days, 250 USD / month up to 10M Spend
Create, edit, preview, and deploy full-stack web apps to a live URL from any MCP client.
Build and publish full-stack web and mobile apps on Floot from any MCP client. Building is free.
Provision, SSH into, run commands on, and manage Linux VPSes from an AI agent. Pay USDC over x402 (Base) or by card over HTTP 402, a running box in under 60s. No signup, no API key to buy. This remote endpoint offers free browse/discovery, quotes, and server status.
AI first app deployment, unlike lovable or figma make, webslop.ai lets you or your ai of choice setup node.js apps or static sites in seconds. Designed be be the perfect place for you to deploy websites and apps super fast to the rest of the world and has a generous free tier.
Build, deploy, and operate hosted web apps on VibeKit (vibekit.bot) from any MCP client.
Deploy a multi-user web app from your agent: hosting, auth, database, and permissions.
Build, edit, publish, and manage websites and web apps with Kleap hosting, domains, and analytics.
Deploy HTML or dist/ to a live HTTPS URL. No account. Drop, MCP, or CLI.
Agent-native web hosting — deploy sites, manage DNS, register domains, scale infrastructure
Build a working web app from a prompt, then deploy it to a live URL.
Deploy a live web app from one sentence. build_app + poll to a public HTTPS URL you own.
Hosting for AI agents: publish a live website in one tool call, ephemeral or forever.
Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?
EU-native PaaS for AI agents — deploy web apps with one sentence, managed Postgres, GDPR by default.
The AWS Knowledge MCP server is a fully managed remote Model Context Protocol server that provides real-time access to official AWS content in an LLM-compatible format. It offers structured access to AWS documentation, code samples, blog posts, What's New announcements, Well-Architected best practices, and regional availability information for AWS APIs and CloudFormation resources. Key capabilities include searching and reading documentation in markdown format, getting content recommendations, listing AWS regions, and checking regional availability for services and features.
The Telnyx MCP server is an official implementation of the Model Context Protocol that enables AI clients (like Claude Desktop, Cursor, and OpenAI Agents) to interact with Telnyx's telephony, messaging, and AI assistant APIs. It provides comprehensive capabilities including making and managing phone calls, sending SMS/MMS messages, purchasing and configuring phone numbers, creating AI assistants with custom instructions, managing cloud storage buckets, scraping and embedding website content, and handling integration secrets. The server exists as both a local implementation and a remotely hosted version, allowing developers to integrate real-world communication infrastructure directly into AI applications.
The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.
