"Linux Foundation" matching MCP servers:

Exposes a Linux host with shell, Python, and filesystem tools as MCP tools over HTTPS, enabling AI agents to execute commands and manage files remotely.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

MCP server to give every agent an ephemeral Linux sandboxes for executing shell commands.

An MCP server that exposes Runloop Devbox operations as tools, enabling AI agents to create and manage Linux sandboxes, execute commands, edit files, snapshot disks, and drive interactive PTY sessions.

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.

A local Model Context Protocol server that allows LLMs to securely execute shell commands on remote Linux and Windows systems via SSH connections.

Provides a local, isolated Linux VM sandbox for AI agents using Apple's Virtualization.framework, enabling fast command execution (~60ms) and package management without cloud costs.

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.

A Model Context Protocol server that integrates Claude with Blender, enabling users to analyze and interact with IFC (Industry Foundation Classes) building models through natural language commands.

Exposes vLLM capabilities to AI assistants, enabling chat completions, model management, and platform-aware container control with automatic detection of Docker/Podman and GPU availability across Linux, macOS, and Windows.

A basic Model Context Protocol (MCP) server implementation that provides a foundation for MCP server development. The README doesn't specify particular functionality, suggesting it may be a template or starting point for building custom MCP servers.

A starter template for building MCP (Model Context Protocol) servers that integrate with Claude, Cursor, or other MCP-compatible AI assistants. Provides a clean foundation with TypeScript support, example tool implementation, and installation scripts for quick customization.

A starter template for building custom MCP servers that can integrate with Claude, Cursor, or other MCP-compatible AI assistants. Provides a clean foundation with TypeScript support, example implementations, and easy installation scripts for quickly creating tools, resources, and prompt templates.

A foundation for building custom local Model Context Protocol (MCP) servers that provide tools accessible to AI assistants like Cursor or Claude Desktop.

A remote MCP bridge that lets MCP clients use Modal sandboxes for Linux execution, dependency installation, Git operations, GPU jobs, and invoking deployed Modal Functions.

A production-ready foundation for developing custom Model Context Protocol (MCP) servers in TypeScript with a complete layered architecture pattern. Includes a working IP geolocation example and comprehensive developer infrastructure to connect AI assistants with external APIs and data sources.

Gives an AI agent its own fleet of disposable Linux microVMs on hardware you control, with tools to spawn, execute commands in, fork from identical disk states, list, and destroy them. Enables safe parallel exploration and cleanup all within an isolated VM boundary.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

Enables AI agents to work in a persistent, isolated Linux workspace with file management, Bash execution, SSH/SFTP access, and durable storage while keeping workloads contained from the host and private networks.

A template for deploying MCP servers on Vercel with example tools for rolling dice and getting weather data. Provides a foundation for building custom MCP servers with tools, prompts, and resources that can be deployed to Vercel's serverless platform.