"Methods for Analyzing Code in a Project" matching MCP servers:

An MCP server to create secure code sandbox environment for executing code within Docker containers.

A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

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.

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

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

Enables headless control of a DOSBox-X guest, including memory reading and patching, framebuffer capture, input injection, and live code tracing without interfering with the host desktop.

Enables running arbitrary JavaScript code in isolated Docker containers with on-demand npm dependency installation, allowing for ephemeral script execution and long-running services with controlled resource limits.

Enables AI-powered creation, configuration, and management of DevContainer environments using natural language prompts. Supports 11+ templates for popular development stacks and provides container lifecycle operations through VS Code, Cursor, or any MCP-compatible editor.

Enables managing GNOME Boxes virtual machines through libvirt/virsh, including lifecycle operations, snapshots, screenshots, and capability-gated keyboard, mouse, clipboard, and drag-and-drop interactions.

Enables running arbitrary JavaScript code in isolated Docker containers with on-the-fly npm dependency installation, supporting both ephemeral one-shot executions and persistent sandbox environments.

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.

A secure Docker-based environment that allows AI assistants to safely execute code without direct access to the host system by running all code within isolated containers.

A Model Context Protocol server for conducting Linux binary analysis and guest system forensics within QEMU virtual machines. It enables automated VM lifecycle management, memory dumping, and interactive debugging workflows for analyzing processes and artifacts.

A server implementation that enables remote Python code execution in Unreal Engine environments, featuring automatic Unreal node discovery and management through a multicast network.

Free, cross-platform VM orchestration for AI workflows with built-in MCP integration, sandboxed code execution, and compliance-ready architecture (SOC 1/2/3, HIPAA, ISO 27001).

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

A powerful, lightweight Model Context Protocol (MCP) server built in Python that enables Artificial Intelligence assistants (Claude Desktop, Cursor, Antigravity, Claude Code, etc.) to manage and monitor your Proxmox VE cluster using natural language.

A Model Context Protocol (MCP) server that enables LLMs to run ANY code safely in isolated Docker containers.

Enables LLMs to safely execute code in isolated Docker containers with resource limits and security controls, supporting session management and automatic dependency installation.

Provides MCP multi-cluster Kubernetes management and operations. It can be integrated as an SDK into your own project and includes nearly 50 built-in tools covering common DevOps and development scenarios. Supports both standard and CRD resources.