"All MCP servers available on the site" matching MCP servers:

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

Enables AI coding agents to run one-shot commands and copy single files to and from remote servers through The Bastion, which authenticates, authorizes, and records each action. Access is controlled by the bastion rather than allowlists or deny lists.

Enables ChatGPT's web interface to operate a real Mac by executing shell commands and reading or writing files over a reverse SSH tunnel, without installing a client or consuming API quota.

Gives ChatGPT hands-on control of a local machine: reading, patching and executing code in approved project folders, running real interactive processes, managing plans and worker sub-chats, and driving the browser or desktop through user-granted permissions. Every capability is a switch inside an approved-folder sandbox, so nothing runs that the user did not explicitly enable.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

Enables ChatGPT to work on a local project by reading and editing files, running shell commands, keeping terminals and desktop sessions open, and splitting work across durable workers whose context persists between tasks. Long-running work can be steered mid-flight, tracked with Goal, and carried into fresh chats via Compact & Resume.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

Exposes persistent, stateful remote Bash sessions to AI agents via SSH, enabling command execution with preserved working directory and environment.

Enables authenticated remote MCP clients to manage a Kali Linux environment, run modular tools in sandboxed or optional host contexts, configure networking, and monitor jobs through a live WebUI.

Automates Ansys Fluent simulation workflows, enabling environment checks, case execution, UDF management, and result export through MCP tools.

An MCP server that lets AI agents list sessions, read terminal screens, type commands, and run commands (with optional waiting for exit status) in Rex terminal blocks on the local machine through the rex CLI. It exposes a single allowlisted passthrough CLI tool plus a guide tool, deliberately excluding destructive or cross-host operations.

Lets an AI assistant look after Android TV boxes, phones and watches over ADB: find devices on the network, see the screen, tap and type, install apps. Package changes are dry-run first, with a protected set read off the device and one-call rollback.

An MCP server that lets AI agents see, act on, and verify the rendered Neovim UI, like a Playwright for Neovim. It provides tools to launch/attach to Neovim, observe the screen, send input, and wait for conditions.

Standalone TypeScript MCP server for micrOS devices. Enables discovering devices, inspecting device cache, running micrOS commands, and discovering each device's available module commands.

Lets Claude manage tmux sessions on Linux — start long-running ML training jobs, check their output, send keystrokes, and kill them.

SSH MCP is a Model Context Protocol tool for managing and interacting with multiple virtual machines over SSH. It simplifies executing commands on remote servers using the standard SSH config file format.

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

Universal Docker MCP server for AI assistants (Cursor, Claude Desktop). Manage Docker containers, execute commands, query databases, and handle environment configurations — all through natural language.

Enables Claude to execute Minecraft commands and get tab completions through the MasterControl API. Allows remote command execution and command discovery while the player is online on a server.

Cross-platform MCP server for policy-controlled command execution on Linux and Windows, with no SSH dependency.

Enables handing one self-contained job to the Claude Code CLI on the local machine and getting back its final message plus a manifest of the artifacts it produced, without letting Claude write into the user's project. Reads are limited to named directories and all writes stay in a throwaway run directory, so the user reviews the listed files and copies in only what they approve.

Delegates coding and read-only exploration tasks to the Antigravity CLI as blocking headless runs, mirroring live progress to on-disk stream transcripts and diffing git status to report touched files and out-of-scope edits. Supports resumable conversations, per-call model/agent/effort overrides, idle and hard timeouts, and discovery of available models and agent profiles.

Enables an AI agent to run local tools on the user's own machine via stdio, including command execution, workspace file read/write, and system status checks.

Enables Claude Desktop to control serial-port devices like network craft ports, radios, rotators, and microcontrollers by sending commands and reading responses until a prompt or available output.

Enables AI models to run interactive tmux terminal sessions that a human can watch and type into, with all output logged and split into searchable per-command regions so only needed lines enter context. Also guides models through unfamiliar tools by returning exit statuses and key output alongside advice on the tool being used.

Runs shell commands inside an existing microsandbox sandbox rather than on the Windows host, tracking the working directory and translating paths between the host project folder and the sandbox mount. Exposes tools for foreground or background execution with timeouts, output retrieval, killing processes, and listing them.

An MCP server for managing Incus virtual machines through structured tools for command execution, file management, and snapshot operations. It enables AI agents to puppeteer VMs on a masternode by wrapping the Incus CLI.

Sandboxed Bash for Agents. Full state capture on every command.

Enables MCP clients to run Cursor CLI agent prompts with any model the installed CLI offers, continue existing sessions, and list available models and sessions. Adds guarded execution with concurrency limits, timeouts, cancellation, and operator-gated auto-approval so multiple models can be run in parallel.