"Understanding Inference Models" matching MCP servers:

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

A free native MCP server for running, understanding, and debugging Linux containers on macOS using Apple's container tool, with audit trail and configurable safety modes.

Read-only VMware vCenter/ESXi monitoring. 8 MCP tools for VM inventory, host status, datastore capacity, cluster info, alarms, events, and VM details. Code-level enforced safety — no destructive operations exist in the codebase. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.

AI-powered VMware vCenter/ESXi monitoring and operations. 20 MCP tools for inventory queries, health monitoring, VM lifecycle management, fast provisioning (Linked Clone, OVA, template deploy), snapshot management, and datastore browsing. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.

Control and automate FlexSim simulations through AI assistants like Claude, enabling manufacturing and warehouse digital twin analysis, parameter studies, and real-time model manipulation via tools for opening models, running simulations, evaluating FlexScript, and exporting results.

Enables AI models to manage Docker containers, images, networks, and volumes through the Portainer API, providing comprehensive container orchestration capabilities.

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 management of homelab infrastructure, including Docker/Podman containers, Ollama AI models, Pi-hole DNS, Unifi networks, and Ansible inventory, with built-in security checks and automated pre-push validation.

A Model Control Protocol server implementation that allows Claude Desktop to use Deepseek models running in Docker, enabling seamless integration between Claude Desktop and Deepseek's language models.

Enables AI models to securely query and manage virtual machines and virtualized resources via the libvirt API through the Model Context Protocol.

A server tool for running Deep Learning models that offers Shell execution, Ngrok connectivity, and Docker container hosting with support for multiple AI frameworks including Anthropic, Gemini, and OpenAI.

Facilitates isolated code execution within Docker containers, enabling secure multi-language script execution and integration with language models like Claude via the Model Context Protocol.

Enables AI models to interact with Harbor container registries to manage projects, repositories, and system configurations in real time. It provides a suite of tools for monitoring health, retrieving statistics, and performing searches across registry data.

MCP servers for managing homelab infrastructure. Monitor Docker/Podman containers, Ollama AI models, Pi-hole DNS, Unifi networks, and Ansible inventory.

An MCP server designed to help AI models refactor Kubernetes configurations by analyzing Kustomize dependencies and rendering manifest diffs across environments. It provides tools for computing file dependencies, rendering overlays, and comparing configuration changes through a checkpointing system.

An MCP server that enables Large Language Models or other MCP clients to interact with Ansys/AGI STK (Systems Tool Kit), allowing users to control STK Desktop simulations programmatically or via natural language.

An Model Context Protocol server that lets language models directly manage and visualize Kubernetes clusters through safe, high-level operational tools.

Enables AI interactions with a running Minecraft server inside a Docker container using RCON, allowing models to programmatically create Minecraft builds and manage the server.