"Using local LLMs for code writing, reviewing, and rule generation" matching MCP servers:

TypeScript stdio MCP server for operating Docker-based local-ydb deployments from AI coding agents. Supports local and SSH-backed profiles, bootstrap, diagnostics, auth hardening, schema permissions, storage workflows, dump/restore, upgrades, and plan-first mutating operations.

Enables AI assistants to interact with local Docker containers, Kubernetes clusters, and system logs using the Model Context Protocol.

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

MCP server that turns natural-language requests into configured n8n workflows and safely operates a local n8n Docker stack, including workflow management, API access, and Docker lifecycle operations with confirmation-based safety.

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.

Create sandboxed local development environments directly from Github and execute tests, see coverage and more! Supports Python, Node, Bun and many test runners.

Enables AI agents to run untrusted, model-generated Python code in a locked-down throwaway Docker container with enforced isolation and resource limits. Supports starting, checking, and stopping asynchronous runs while returning structured status reports without exposing the host, network, or Docker controls.

Enables Docker container management through natural language conversations, including deployment, health monitoring, dependency resolution, auto-redeployment on file changes, and environment snapshots.

Enables Docker container management and test execution via MCP tools, supporting image building, container operations, and automated test runs.

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.

Enables AI coding assistants to search local log files, inspect Docker containers, and clean up JSON payloads through a local stdio MCP server.

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.

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.