"Information about Ansible - IT automation tool" matching MCP connectors:

Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?

Build a landing page from your IDE chat, publish it, then manage domains and analytics.

Deploy a GitHub repo to a live HTTPS URL from your AI tool; read logs, set variables, resize apps.

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 BigQuery remote MCP server is a fully managed service that uses the Model Context Protocol to connect AI applications and LLMs to BigQuery data sources. It provides secure, standardized tools for AI agents to list datasets and tables, retrieve schemas, generate and execute SQL queries through natural language, and analyze data—enabling direct access to enterprise analytics data without requiring manual SQL coding.

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 Compute Engine MCP server is a fully-managed Model Context Protocol server that provides tools to manage Google Compute Engine resources through AI agents. It enables capabilities including instance management (creating, starting, stopping, resetting, listing), disk management, handling instance templates and group managers, viewing machine and accelerator types, managing images, and accessing reservation and commitment information. The server operates as a zero-deployment, enterprise-grade endpoint at https://compute.googleapis.com/mcp with built-in IAM-based security.

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.

CloudOracle - 14-tool multi-cloud compliance MCP: AWS, Azure, GCP posture, IAM, configs.

Deploy static sites on Hostsmith - give it a file, get a live HTTPS URL. EU/US residency.

Backend for vibe coders. Connect Butterbase to any MCP-compatible AI coding tool and provision a full backend automatically — database, authentication, file storage, edge functions, and real-time — from a natural language prompt. No SQL, no configuration, no backend knowledge required. Free to start at butterbase.ai.

Protocol-native energy infrastructure orchestration for AI data centers. Provides 46 MCP tools across 8 grid protocols (IEC-61850, DNP3, Modbus, OCPP, OpenADR, IEEE 2030.5, IEC 60870-5-104, ICCP) with 5 core API primitives: connect, dispatch, settle, comply, and intel. Enables AI agents to programmatically interact with substations, grid interfaces, and energy assets for real-time workload-grid coordination.

Give your AI coding assistant a backend to deploy to. WiseWall turns a static site into a real product — magic-link accounts, a per-member database, Polar-powered payments, and a server-side paywall — and this package lets your coding agent drive all of it: deploy, configure a custom domain and DNS, manage secrets, create plans, without ever opening a dashboard.

Run, debug, and triage tests via natural language across HyperExecute, Automation, SmartUI, and Accessibility on the TestMu AI cloud.

Talk to your LLM and get a live web app deployed to a real URL.** onvibe.run is a conversational PaaS: you describe the app you want, the LLM builds it through MCP tools, and it ships to a public URL like `https://your-project.onvibe.run` — no dashboards, no config files, no manual deploys.

Static-site hosting via MCP — ask your AI client to build a site (lands at .beam.page or your custom domain), then update it anytime, from anywhere, just by asking again.

The OpenMesh MCP Server provides decentralized, permissionless cloud infrastructure that integrates AI assistants with Web2 and Web3 applications without middlemen. It offers intelligent service discovery to identify MCP servers, acts as a universal proxy for routing requests to discovered services, implements performance optimization through usage feedback, and provides automatic fault tolerance with alternative services when servers become unavailable.