"How to find people on LinkedIn using their profiles" matching MCP servers:

An MCP server that enables searching for specific files by name within the current directory and its subdirectories. It uses Server-Sent Events (SSE) to provide a find_file tool for locating local files and libraries.

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.

Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.

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.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

Enables AI assistants to diagnose, troubleshoot, and manage PC settings on Windows, macOS, and Linux through natural language commands.

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.

An MCP server that lets Claude query Google's Gemini CLI as a sub-agent. Get second opinions, verify information, and cross-reference answers between AI models.

Enables arithmetic operations (add, subtract, multiply, divide) through a custom Model Context Protocol implementation, containerized with Docker for easy deployment.

Enables cloud agents to securely operate local machine resources (files, commands, screenshots) via standard MCP protocol.

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.

Wraps Kali Linux penetration testing tools for authorized security assessments, driven by a local LLM via LM Studio.

A simple MCP server that exposes a terminal tool, allowing AI agents to execute shell commands.

An MCP server for Hyprland that enables AI agents to control workspaces, windows, mouse, keyboard, and take screenshots on a Wayland desktop.

A cross-platform screenshot tool that lets coding agents capture and view their output, enabling self-correction through visual feedback.

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.

A server that enables LLMs to securely manage and execute commands on remote SSH servers.

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

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.

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

Enables AI assistants to execute shell commands and transfer files via SFTP across remote servers using existing SSH configurations. It supports parallel execution on server groups and provides built-in safety warnings for potentially destructive commands.

A simple MCP server that provides a greeting tool using FastMCP, with support for both local and containerized deployment.

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.

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

An MCP server that enables AI clients to execute shell, Python, and Node commands on the local machine across platforms.

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