"Finding people on LinkedIn by name" 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.

An interactive coding agent and MCP server that provides access to various AI models via the Tsinghua University lab proxy API. It enables users to inspect files and execute shell commands within their local directory using models like DeepSeek, GLM, and Qwen.

Enables AI agents on macOS to retrieve current battery levels and charging status for AirPods, iPhone, mice, headphones and speakers tracked by AirBattery, optionally filtering by device or including Nearcast devices. It exposes a single read-only MCP tool over stdio for compatible clients such as Codex and Claude.

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 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.

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.

Runs commands on machines you cannot SSH into by publishing steps to a transport the far side already reaches (git, file share, S3, relay), then reads back a log with every line timestamped in UTC. Seven tools cover send, status, logs, stall detection and a pre-flight check.

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

Orchestrates multiple Slidev presentations by managing dev servers and proxying Slidev's MCP tools for targeted presentations.

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

Enables Claude Code to interact with Linux X11 desktops by performing mouse actions, keyboard input, and capturing screenshots. It provides a suite of tools for automation tasks such as clicking, typing, and zooming on specific screen regions.

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 AI assistants to control Mac sleep settings by preventing sleep for configurable durations and modes using natural language commands.

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.

Opt-in, token-authenticated MCP server built into the Shelly Android terminal app: read-only tools for terminal output, git status, registered agents and repos on the phone, plus off-by-default run_command and write_file that need an on-device approval tap per call.

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.

MCP server for Webmin system administration. 61 tools across 12 modules covering system monitoring, services, users, cron, packages, files, storage (SMART + LVM), security (Fail2ban), MySQL databases, Webmin ACL, and disk quotas. Four-tier safety framework with safe mode on by default. Python, MIT license, Docker and local deployment supported.

Enables AI agents to look up stored logins by URL, name, or alias and use them without seeing the secrets, injecting authentication into HTTP requests, running commands with credentials in the environment and scrubbed output, and fetching 2FA codes, subject to per-credential policies and user approval.

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.