"Deploying a Website Using BaoTa (BT) Panel" matching MCP servers:

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Enables AI to execute registered system commands across platforms using a stable program + args interface, without requiring shell-specific syntax or tool discovery.

Enables reading diagnostic data from remote servers over SSH using a whitelist of read-only commands, with secret redaction.

Enables AI assistants to perform Active Directory reconnaissance by enumerating users, groups, computers, trusts, and password policies using ldapdomaindump on a remote Kali host via SSH.

Enables AI assistants to perform web content discovery scans using feroxbuster on a remote system via SSH, with support for recursive scanning, filtering, and background execution.

Enables interaction with Railway cloud platform through the CLI to manage projects, services, deployments, and environments. Supports creating projects, deploying templates, managing environment variables, and monitoring logs through natural language commands.

MCP server that lets AI clients manage a Qinglong (qinglong) panel via natural language, covering crons, environment variables, scripts, subscriptions, logs, configs, and dependencies through its Open API.

A Model Context Protocol server that connects to a WISP game panel, letting AI clients inspect and manage game servers (state, files, console, backups, databases) with read-only defaults and opt-in capabilities.

Using MCP to run code via e2b.

Enables remote MCP clients to access local filesystem and shell commands by deploying a Cloudflare Worker relay and a local daemon, providing tools like read/write files, exec commands, git status, etc.

Pixel-level browser automation MCP server that drives a real Chrome browser using screenshots as vision input and OS-level mouse/keyboard as output, evading anti-bot detection.

A secure, local communication runtime bridge that interfaces a cloud-based Large Language Model (Claude Desktop) with a local machine execution environment using the Model Context Protocol (MCP).

Enables an MCP-capable agent to operate a heterogeneous cluster of Debian/Armbian Linux nodes over SSH from a single inventory, inspecting status and logs, managing packages, services, files, storage and NFS, and deploying new capabilities to nodes through installable modules. Built-in cluster tools fan out to nodes by explicit names, roles or tags with bounded concurrency, while modules can be installed on compatible nodes and run on demand or as systemd services.

MCP server that lets AI agents call APIs without ever seeing the credentials, using a local encrypted vault and per-secret allowlist policies for HTTP requests and subprocess environment variables.

A lightweight MCP server for file manipulation, code searching, and shell command execution, with optional semantic search using local embeddings.

Enables web-based AI agents such as claude.ai, ChatGPT and Grok to read and edit files and run allowlisted shell commands on your own machine, plus control Chromium, DevTools, ports, git, SQLite and background tasks. Access is exposed over HTTPS with OAuth 2.1 through a swappable public edge (Tailscale Funnel or a Cloudflare tunnel), with a loopback-only control panel for configuration.

Turns Markdown files into local MCP servers, enabling users to define and run tools using simple Markdown syntax with zero dependencies.

Enables local code execution via Codex (Luna) through MCP, using ChatGPT Web conversations as a planner. Provides file, terminal, and code execution tools while keeping long-running jobs manageable.

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.