"Managing Proxmox Servers" matching MCP servers:

A Model Context Protocol server that enables interaction with PostgreSQL databases for analyzing setups, debugging issues, managing schemas, migrating data, and monitoring performance.

Connects AI agents to microsandbox for creating lightweight sandboxes, executing code, managing files, and monitoring resources.

A Model Context Protocol server implementation that enables secure remote command execution via SSH, with features for managing and using SSH credentials.

A comprehensive system for managing AI-assisted agile development workflows with a modern, resource-based API using FastMCP.

Enables managing E2B cloud sandboxes, templates, filesystems, and processes through Model Context Protocol tools.

An MCP server that allows Claude Desktop to remotely control Claude Code instances for executing commands and managing files.

Enables managing local repositories, CLIs, MCP servers, and skills via MCP tools, with inventory tracking, guarded updates, and Docker-sandboxed trials.

Provides a persistent Python REPL session as a tool for executing code, managing files, installing packages, and initializing projects via the MCP protocol.

Enables WebGPT to delegate durable coding-project tasks to a local Luna worker over MCP, managing sessions, tools, permissions, memory, and recovery while preserving at-most-once execution.

Enables LLM agents to perform complete database operations on SQLite databases, including creating tables, executing queries, and managing data through CRUD operations with schema inspection capabilities.

An MCP server that allows managing Docker containers through natural language, enabling users to compose, introspect, and debug containers without running commands themselves.

A Model Context Protocol server that allows integration with Claude Desktop by creating and managing custom tools that can be executed through the MCP framework.

Context-Pods is a comprehensive development framework for creating, testing, and managing Model Context Protocol (MCP) servers. It provides a Meta-MCP Server that can generate other MCP servers through natural language descriptions or by wrapping existing scripts.

Provides MCP tools for managing disposable Docker sandboxes that let AI agents safely execute commands in isolated, ephemeral environments.

A server implementation of the Model Context Protocol (MCP) that provides REST API endpoints for managing and interacting with MCP resources.

Enables AI assistants to interact with the MetaTrader 5 trading platform for market data analysis, placing trades, and managing trading positions. Provides comprehensive access to forex and financial market operations through the Model Context Protocol.

Enables AI assistants to interact with the Zerodha trading platform for placing stock orders, viewing portfolio holdings, and managing mutual fund investments. Provides secure OAuth authentication and real-time trading capabilities through Zerodha's official API.

Exposes MetaCall FaaS capabilities as MCP tools for deploying, invoking, and managing serverless functions.

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.

Lets an AI agent read and change on-premises Active Directory by writing short JavaScript scripts that run in a network-isolated sandbox against a chosen domain. Runs on Windows as the logged-on user, over Kerberos, with tools for executing scripts, searching the domain's schema catalogue, querying Microsoft Learn docs, and managing domain connections and Group Policy objects.

Provides structured spec-driven development workflow tools for AI-assisted software development with sequential spec creation (Requirements → Design → Tasks). Features a real-time web dashboard for monitoring project progress and managing development workflows.

Runs AI-generated code in secure Firecracker microVMs with opt-in network policy enforcement, PII scanning, prompt injection defense, and audit logging. Exposes MCP tools for running commands, managing files, and the full sandbox lifecycle.

Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.

A foundational project for quickly developing Model Context Protocol servers using the TypeScript SDK and Zod for schema validation. It features pre-implemented examples for tools like a calculator and greeting service, along with templates for managing dynamic resources.

A Model Context Protocol server that enables running and managing long-running background tasks (like development servers, builds) from within Claude Desktop or other MCP-compatible clients.

AI-powered MCP server for connecting and managing Jupyter Notebooks. Enables interactive code execution, multi-notebook management, and multimodal output for data analysis, visualization, and machine learning.

Enables inspecting and editing live marimo notebooks via a FastMCP server, offering tools for managing cells, variables, and execution.

Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.

Enables AI agents to interact with the Baltamatica scientific computing kernel, executing code, managing variables, and running scripts while preserving workspace state across calls.

Provides a secure, sandboxed interface for LLM agents to interact with HPC clusters via bubblewrap isolation, managing workspaces and executing commands locally or through Slurm.