"A service for predicting triathlon results based on training data" matching MCP servers:

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Provides secure access to containerized build environments for software projects, enabling AI assistants to execute builds, run tests, manage git operations, and inspect build artifacts without requiring local installation of dependencies.

Enables container orchestration on the local Docker daemon, allowing management of jobs and services via MCP tools.

A VMware ESXi/vCenter management server based on MCP (Machine Control Protocol), providing simple REST API interfaces for virtual machine management.

MCP server that integrates with Coolify to let AI assistants manage Coolify instances via a clean toolkit wrapping the official REST API.

A Node.js application that provides a JSON-RPC interface to interact with CO2 sensor data, working in both simulation mode and with real Raspberry Pi Pico hardware connections.

Enables AI agents to inspect pending updates and service health for Proxmox VE VMs and containers, then take snapshots, apply official updates, reboot, and roll back under tag-based permissions and human-confirmed risky actions.

GenieACS-MCP is a Go-based MCP server that bridges any GenieACS (TR-069 ACS) instance, exposing device data, firmware management, and CPE actions (reboot, parameter refresh, firmware download) over JSON-RPC

Enables AI agents to run CP/M, MP/M, and DOS packages on Z80/x86 emulators, inspect byte-exact results and files, and debug the emulators themselves over the Model Context Protocol.

Gives AI assistants full control over a VPS via SSH, enabling command execution, file management, service control, Docker and firewall management.

Enables AI assistants to manage homelab infrastructure through automated service installation (Jellyfin, Pi-hole, Ollama, Home Assistant, Frigate NVR), VM operations, AI accelerator support (MemryX, Coral TPU, Hailo-8), and Terraform state management with SSH-based discovery and deployment.

Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9

Enables AI assistants to provision and manage cloud infrastructure and AI/ML workloads—such as GPUs, nodes, storage, networking, databases, Kubernetes, and training/inference resources—through natural language. It also provides a universal REST tool for authenticated access to the underlying cloud API.

Enables AI assistants to execute commands on a Proxmox host via SSH with built-in security blocks for destructive operations. It supports key-based authentication and provides a dedicated tool for remote server management tasks like listing virtual machines and containers.

Provides a secure MCP interface to execute commands inside Docker Compose service containers, with real-time output capture and configurable timeouts.

An MCP server that enables agents to attach debugpy to running Python processes inside Docker containers for enhanced debugging and inspection. It provides tools for container autodiscovery, process injection, and generating breakpoint plans based on logs and metadata.

Enables control of a home lab through a single MCP server, exposing tools for Home Assistant, Portainer, Sonarr, Radarr, SABnzbd, and Jellyfin so Claude can query states, manage containers and stacks, handle media libraries and download queues, and run automations. Each service is optional and can be configured via environment variables, with a read-only mode and bearer-token-protected HTTP transport for always-on deployments.

Enables interaction with the CoreHub cloud platform to manage containers, EPFS filesystems, distributed training, and inference services through MCP tools.

A simple MCP server that allows accessing and executing shell commands on a VM machine through a web-based terminal interface, with automatic tunneling to make the VM accessible from anywhere.

Enables managing RunPod compute for the Learning-to-Swim replication through natural language, including pod lifecycle, SSH/rsync file transfer, detached training jobs, and supervised runs with cost guardrails.

A Python-based server enabling interaction with Proxmox hypervisors. It supports secure authentication and provides tools for managing nodes, VMs, clusters, and storage.

A Python-based MCP server for interacting with Proxmox hypervisors, enabling management of nodes, VMs, containers, and executing commands via QEMU Guest Agent.

Enables LLMs to remotely control VirtualBox VMs and Playwright browsers on Windows, including VM lifecycle actions, in-guest commands, browser automation, window management, and service monitoring via REST API and MCP.

Enables comprehensive management of Vast.ai GPU cloud instances, including searching for GPU offers, creating and managing instances, executing remote commands via SSH, and monitoring background tasks for ML training workflows.

Exposes Proxmox VE hosts as MCP tools for inventory, status, and VM/container management, running as a standalone Streamable HTTP service.

An MCP server that enables management and deployment of Ludus lab environments through natural language commands. It provides comprehensive tools for range lifecycle management, configuration validation, and documentation research within virtualized training infrastructures.

Enables LLMs to dynamically orchestrate containerized application deployments to a Kubernetes cluster, handling configuration validation, manifest generation, dry-run planning, and service endpoint extraction.

A Model Context Protocol server that enables natural language control of Ludus cybersecurity training environments, allowing users to deploy, manage, and configure virtualized security training ranges.

Enables monitoring and management of Azure resources including Virtual Machines (VMs) and Virtual Machine Scale Sets (VMSS) through a RESTful API with secure Service Principal authentication.

Provides comprehensive management of TrueNAS SCALE instances through 278 actions across 18 categories using a token-efficient hierarchical tool design. Users can perform tasks like storage management, service configuration, and system monitoring while benefiting from built-in safety confirmations and read-only dashboard resources.