"Yandex Cloud" matching MCP servers:

A thin MCP server that delegates lightweight tasks from Claude Code or any MCP-compatible client to local or cloud LLMs via LiteLLM, supporting models like Ollama and cloud APIs as subagents.

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

Enables AI agents to discover, evaluate, and provision cloud infrastructure across AWS, GCP, and Azure with cross-cloud normalization, cost comparisons, and deployable execution kits.

A Model Context Protocol (MCP) server that integrates Claude with the Terraform Cloud API, allowing Claude to manage your Terraform infrastructure through natural conversation.

Enables MCP-compatible AI agents to deploy applications to Google Cloud Run by providing tools for deploying code, listing services, and managing Google Cloud projects.

Enables management of Verda Cloud GPU instances through Claude, allowing users to deploy spot instances, attach volumes, and monitor status. It supports automated workflows for checking availability and configuring instances with startup scripts.

MCP server for SkyPilot that lets LLMs manage cloud clusters, jobs, and storage through the Model Context Protocol.

MCP Server for Google Cloud Healthcare API enables Agentic AI for a variety of FHIR-based digital health solutions, from smarter clinical workflows for Health Systems to Pre-Auth frameworks for Payers!

Enables deploying applications and managing cloud resources in Timeweb Cloud through natural language.

Enables AI assistants to interact with Google Cloud Platform resources through natural language queries. Supports querying and managing GCP services like Compute Engine, Cloud Storage, BigQuery, and more across multiple projects and regions.

Enables any MCP client to triage cloud agents, projects, conversations, transcripts, pull requests, and files, including listing agents, reading transcripts, following runs, and sending follow-ups, using an API key or browser sign-in.

Enables AI assistants to spawn and manage long-running cloud agents via MCP, offloading tasks to AWS Bedrock AgentCore.

Enables agents to deploy, run, expose, inspect, and manage isolated cloud environments, including databases, caches, browsers, GitHub-hosted apps, and arbitrary OCI images, via MCP tools.

A CLI and cloud platform providing managed hosting for MCP servers with intelligent tool filtering to reduce token costs and improve LLM accuracy. It serves as a secure proxy that connects AI clients to cloud tools while keeping sensitive credentials on the local machine.

Coordinates specialized agents (Architecture, Quality, Cloud, Prompt) to plan, build, test, and deploy applications with self-healing capabilities, authentication, and analytics for autonomous software engineering workflows.

Enables creating and running production-grade Model Context Protocol servers for REST APIs, GraphQL endpoints, OpenAPI specs, Google Cloud services, and custom Python logic from a declarative JSON blueprint, with built-in authentication, response shaping, multiple transports, and one-command Cloud Run deployment.

Provides AI agents with cloud-based execution environments through Alibaba Cloud's Wuying infrastructure, enabling browser automation, file operations, and terminal access in secure, serverless cloud environments.

A secure MCP (Model Context Protocol) server hosted on Google Cloud Run that enables team collaboration by providing authenticated access via Google Cloud IAM, allowing teams to share custom MCP servers over the internet before official MCP authentication is implemented.

A cloud-only stdio MCP server that lets local clients spawn, message, inspect, and stop remote agent threads executing on Cloudroom Cloud VMs through room-cli. Supports GitHub-repository-backed or Personal workspaces with explicit provider, model, and reasoning settings.

Exposes the Ollama SDK as MCP tools, letting MCP-compatible clients manage local and cloud models, run chat/generation/embeddings, and perform cloud-backed web search and fetch.