"AI-powered storage solutions or AI-assisted tools for driving" matching MCP servers:

AI-powered VMware storage management for vSphere. Manage datastores, iSCSI targets, and vSAN via natural language with 11 MCP tools.

A Model Context Protocol (MCP) server that exposes the EasyDeploy public REST API as tools for Claude, Cursor, Claude Code, and other MCP clients.

Enables discovery of public API operations, scoped read-only diagnostics for domains, DNS, and mail, and a controlled write lifecycle that requires independent human approval before any mutation.

Enables AI assistants to deploy and manage hosted apps from git repos, read logs, add Postgres databases and domains, manage API keys and budgets, and send requests to 200+ AI models. Connects over remote Streamable HTTP with OAuth sign-in, so users need no API keys, installs, or local server.

Enables interaction with Google Cloud Storage buckets and blobs through an MCP server, supporting operations like listing, uploading, searching, batch operations, and generating signed URLs.

MCP server that lets an AI agent manage Proxmox VE in natural language, with policy-driven security, read-only mode, two-step confirmations, and audit logging.

Intelligent AI routing and integration platform for seamless provider switching

Enables AI applications to interact with decentralized storage through a standardized Model Context Protocol interface, allowing file uploads, retrievals, and identity management.

Enables AI-powered image and video analysis using Google Gemini and Vertex AI models. Supports analyzing single or multiple images, detecting objects with bounding boxes, and video content analysis through natural language prompts.

A Python CLI package aaws published to GitHub with PyPI distribution via GitHub Actions. Natural language in → AWS CLI command out, with explain, confirm, and safety layers. Available as MCP server.

Enables natural-language management of Kubernetes clusters via kubectl-ai and Gemini, providing commands like listing pods, scaling deployments, and retrieving logs through a FastAPI backend.

Enables AI agents to access Cloudflare Workers AI for serverless LLM chat completions, text embeddings, and image generation via MCP tools.

An MCP server that enables running commands against a ServiceNow instance via its REST APIs, including Table, Aggregate, Attachment, Import Set, Batch, CMDB, Service Catalog, Change Management, and Knowledge APIs.

Implementation of Model Context Protocol (MCP) server that provides tools for accessing Google Cloud's Vertex AI Gemini models, supporting features like web search grounding and direct knowledge answering for coding assistance and general queries.

Deterministic AI data-center design tools for sizing, validation, and conceptual rack/site layouts. Supports NVIDIA Hopper, Blackwell, and Rubin profiles. Calculations require a registered AIDC API key; results preserve warnings, RFIs, and pending validations.

Enables MCP-compatible clients to search approved local Markdown runbooks, retrieve selected local host health details, and get bounded Kubernetes pod-status summaries for allowlisted clusters and namespaces.

Provisions Google Analytics 4 for local AI/web projects by creating properties and web data streams, injecting gtag snippets, and saving configuration.

Enables AI assistants to manage Amazon SageMaker AI resources including endpoints, jobs, pipelines, MLflow tracking servers, domains, models, model cards, and apps.

Enables comprehensive integration with Azure AI services including OpenAI, Cognitive Services, Computer Vision, and Face API through a mission-critical MCP server. Provides enterprise-grade reliability with high availability, observability, chaos engineering, and secure multi-region deployment capabilities.

Exposes SAP AI Core APIs as MCP tools, enabling AI assistants to manage AI Core lifecycle and administration through natural language.