"RAD Studio" matching MCP servers:

Studio MCP transforms any CLI command into an AI tool by using a simple template syntax to define input schemas and arguments. It enables AI agents like Claude and Cursor to execute local scripts and system commands through a dynamically generated Model Context Protocol server.

An MCP server that enables LLMs to compile LaTeX documents and inspect the resulting PDF, supporting an autonomous write-compile-check-revise loop via a self-hosted Overleaf CLSI instance.

Enables AI assistants to deeply integrate with RStudio for environment management, code execution, project management, and package management.

Enables interaction with a persistent PowerShell session through LM Studio. Provides tools to run commands, manage directories, and handle environment variables while maintaining session state between calls.

A starter MCP server using StdioServerTransport, providing example tools to check which app runs on a port (macOS) and add two numbers.

Exposes any OpenAPI spec endpoints as AI agent tools via stdio, requiring no code generation or maintenance.

Wraps Kali Linux penetration testing tools for authorized security assessments, driven by a local LLM via LM Studio.

MCP server for Decky Loader plugin development, providing tools to build, deploy, debug, and capture screenshots/recordings on a Steam Deck via commands like deck.deploy and deck.captureScreenshot.

Enables an AI agent to run shell commands and move files inside a WSL distro on the same Windows machine via wsl.exe, with no sshd, key, or port required. Each pre-registered distro-and-user entry enforces guard policies limiting dangerous commands, Windows interop, write targets, and accessible paths.

Terminal\[X]MCP is a Model Context Provider (MCP) server that enables intelligent terminal automation through a multi-agent system with distributed specialized roles for command execution, security validation, and real-time monitoring.

Enables AI agents to manage a homelab by providing tools for Docker, Ollama, and system monitoring through the Model Context Protocol.

Enables AI agents to safely explore and diagnose remote servers by providing a read-only sandbox with controlled access to files, logs, Docker, and databases. It exposes MCP tools that allow natural-language investigation and direct command execution without write permissions.