"Finding people named Altman on LinkedIn" 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 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.

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.

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

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.

Enables MCP clients to safely read, write, edit, search, and optionally run commands within one or more named project workspaces, while maintaining a work journal and tracking changes.

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

Stateful, structured, safe shell sessions for AI agents, on real infrastructure.

A cross-platform MCP server providing secure, user-approved privilege escalation for Cursor agents, with tools for running commands as admin on Windows and root on Linux.

Enables AI assistants to manage VMware Fusion virtual machines on macOS using the vmrun CLI, including starting, stopping, and snapshot operations.

Enables AI agents to read tmux pane content on-demand, providing context-aware assistance during interactive terminal sessions.

A secure remote server management tool based on MCP protocol, supporting SSH connections, command execution, and SFTP file transfers.

Enables LLM clients to execute commands and transfer files on SSH hosts via a named registry, supporting direct, ssh3 (QUIC), and WSL-proxied transports.

Enables AI assistants to execute SSH commands and perform token-efficient file operations on remote servers via the Model Context Protocol.

Enables running shell commands on a Hostinger VPS via SSH directly from the Claude Code chat interface.

An MCP server that exposes a single tool, jq, for running jq filters against JSON files on disk.

Provides ripgrep search capabilities to MCP clients like Claude, enabling high-performance text searches across files on your system.

Enables headless, commandlet-based control of Ascent's Unreal project through small named tools for running scripts, probing and editing actors/assets, managing maps, materials, Ultra Dynamic Sky presets, importing assets, taking screenshots, and verifying workflows with safeguards.

Lets an AI assistant check on a ZimaBlade or any Docker host over plain SSH (load, top processes, container stats, logs, disk) and restart only allowlisted containers. Nothing to install on the box.

For people who want their AI to run the build, read the error and check the dev server itself, instead of pasting output into chat. Works with Claude Desktop (one-click installer), Cursor, Claude Code and Cline. Runs locally over stdio or HTTP, no telemetry. A seatbelt for everyday mistakes, not a sandbox.

Enables self-hosted local file, terminal, document, and named-device tools for MCP clients, with an isolated document mode and a full-access mode.

Provides ripgrep search capabilities to MCP clients like Claude, allowing high-performance text searches across files on your system.

An MCP server that allows AI models to execute system commands on local machines or remote hosts via SSH, supporting persistent sessions and environment variables.

An MCP server that plays local sound files on macOS using the afplay command, allowing AI assistants to trigger audio notifications after responding.

A Model Context Protocol server that captures and manages stdout logs through named pipes, making application output available for querying and debugging in AI tools like Cursor IDE.

Enables SSH remote command execution on remote machines with persistent connections, supporting automatic key discovery and connection pooling.