"Information on LinkedIn Business or LinkedIn Advertising" 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.

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.

Enables AI agents to run WP-CLI commands on WordPress sites, including byte-faithful post and meta copying with checksum verification, over local Docker, Pantheon Terminus, or SSH.

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.

Enables AI assistants to understand lab topologies, follow operational principles, and interact with real network devices through observable terminals while keeping private access information hidden.

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

Enables ChatGPT to read and edit local text files, apply precise string replacements, and run Bash commands on a user's own macOS or Linux machine through a secure local tunnel without exposing public ports.

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

Durable MCP server for managing long-running jobs locally, over SSH, or on Slurm clusters. Jobs survive client disconnects and return exit codes, bounded logs, and JSON artifacts.

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.

Enables a coding agent to get short, token-efficient answers about a project through grouped searches, focused symbol or section reads, and bounded read-only script output, with safety limits on paths, secrets, commands, and response size.

Enables AI assistants to manage remote servers via SSH with 14 commands for execution, file transfer, auditing, and monitoring.

Enables users to run remote commands, inspect projects, transfer files, and execute scripts on authorized Linux servers through natural-language tool calls. It supports listing servers and groups, executing commands individually or across groups, and uploading or downloading files over secure connections.

Made for Amiga development: an AI agent builds on the PC and tests on a real Amiga (AmigaOS 2.04+, any 68000) or FS-UAE over the network. Run commands, copy files, take screenshots, drive mouse and keys, click buttons and pick menus by name (MUI, ReAction, GadTools), wait for windows instead of guessing, send ARexx, and check a PiStorm’s temperature or the last crash. 30 tools.

An MCP server that gives AI coding assistants a remote_exec tool to run shell commands on a remote computer through a relay, with supervised approval for each command. The remote machine only needs curl and bash, with no SSH access or installed agent required.

mcp-node-zig is an MCP server for remote machines. Drop it on a build box, a homelab server, a Windows host or a VPS, and any MCP client can run commands, drive long-running processes and read and write files there over one authenticated HTTP endpoint.

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.

A minimal MCP server that exposes a single tool to query local hardware information (OS, CPU, memory, architecture).

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

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

Let your AI build and run a whole app on your computer: an online shop, website, booking app or AI helper. It creates the parts, starts them, checks they work and fixes problems.

Enables AI assistants to execute malware analysis tools on a REMnux system via Docker, SSH, or local connections. It provides automated file-type analysis, structured tool discovery, and security guardrails for streamlined malware investigation.

An MCP server that intelligently filters and compresses tool outputs to reduce context window usage, saving up to 90% of tokens by removing noise such as passing tests and redundant information.

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.