"Self-hosted MCP server on Proxmox LXC container accessible remotely from AI clients" matching MCP servers:

A secure, container-based implementation of the Model Context Protocol (MCP) that provides sandboxed environments for AI systems to safely execute code, run commands, access files, and perform web operations.

A remote MCP server (Node.js/TypeScript) deployed on Azure Container Apps that provides todo list management tools with JWT authentication and role-based access control.

An MCP server for Proxmox VE that enables read-only cluster inspection, VM/container lifecycle operations, snapshots, migration, and provisioning with safe confirmation gates.

Provides read-only Proxmox cluster oversight and configuration compliance checks through MCP, covering health, inventory, storage, backups, snapshots, and updates.

Enables read-only interaction with Proxmox homelab VMs and containers, allowing LLM agents to list VMs, monitor status and performance metrics, view snapshots, and check cluster health through natural language queries.

A Model Context Protocol server that enables interaction with self-hosted Supabase instances, allowing developers to query database schemas, manage migrations, inspect statistics, and interact with Supabase features directly from MCP-compatible development environments.

A protocol server that enables interaction with self-hosted Supabase instances directly from development environments, allowing database introspection, management of migrations, auth users, and storage through MCP clients like IDE extensions.

An MCP server for managing and monitoring Docker, Docker Compose, and Kubernetes environments alongside Azure Application Insights. It enables advanced log filtering, container lifecycle management, and querying of cloud application traces and metrics.

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

Enables agents to reflect on their own thinking by returning a metathought question based on a deterministic selection from curated cognitive lenses.

Give Claude direct access to your AWS account, SSH into your servers, run shell commands on your laptop, query your databases, and manage PM2 processes — all from a Claude chat. No Claude Code subscription needed. Your keys never leave your machine.

A Model Context Protocol (MCP) server that provides unified access to one's professional profile, including experience, publications, career timeline, and social media presence.

Enables AI assistants to interact with Self, a self-awareness framework that connects daily actions to personal values, missions, and goals. Supports tracking foundations, intentions, projects, obstacles, and daily reflections through natural language.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Manages Proxmox VE clusters through the official PVE API with 22 tools for cluster status, VMs/containers, storage, snapshots, and provisioning. Supports stdio or HTTP/StreamableHTTP transports with optional OAuth for Gemini and multi-server configurations.

Enables developers to interact with self-hosted Supabase instances, providing database introspection, migration management, auth user operations, storage management, and TypeScript type generation directly from MCP-compatible development environments.

Enables read-only searching and retrieval of the official Proxmox VE administration guide via MCP tools and resources, returning cited fragments with source URLs and freshness metadata.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

Enables interaction with self-hosted LLM models via Ollama and Supabase database operations. Supports text generation, SQL queries, and data storage/retrieval through natural language commands.

Enables autonomous learning from interactions through pattern recognition and machine learning techniques. Continuously improves performance by analyzing tool usage, providing predictive suggestions, and sharing knowledge across MCP servers.