"How to provide access to Chrome's developer tools" matching MCP servers:

Enables AI agents to control and interact with a local Windows computer through authenticated MCP tools, including file operations, shell commands, process management, HTTP requests, and system/media inspection.

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 SSH and UART/serial port access for Claude Code to directly control remote devices like Raspberry Pi, embedded systems, and IoT devices. Supports command execution, file transfers via SFTP, and serial communication.

A production-grade MCP server for Windows developer environments, providing AI assistants with secure terminal, filesystem, git, Docker, SQLite, browser, and GitHub capabilities through 12 providers and 40+ tools.

Local macOS MCP bridge that gives ChatGPT shell, unrestricted filesystem access, real PTY sessions, background jobs, and read-only stored Codex history. ChatGPT stays the reasoning layer; the bridge makes no model calls.

A local MCP runtime for macOS and Windows that enables ChatGPT to read, edit, search, run tests, and capture screenshots in your local project folder while keeping your source code on your machine.

Turns any Linux server into an AI-agent-accessible machine over HTTPS, allowing MCP clients like ChatGPT, Claude, and Grok to securely control files, run shell commands, inspect system state, query SQLite, and work with git behind a bearer token.

Enables cloud services with MCP support, such as Notion AI, to read, search, edit, create, and delete files within a single designated folder on your computer, and to run only allowed commands.

Provides full access to a local Windows computer via MCP, enabling arbitrary command execution, file operations, and process management through a secure stdio or HTTP tunnel.

A passive MCP server that exposes a toolbox of executable tools (shell, network, HTTP, AI search, SSH, S3 file operations) to autonomous agents via Streamable HTTP, with strong security features including Docker sandboxing and WAF.

An MCP (Model Context Protocol) server implementation using HTTP SSE (Server-Sent Events) connections with built-in utility tools including echo, time, calculator, and weather query functionality.

Enables web ChatGPT to drive durable, sandboxed Claude Code sessions on a local Mac, with controlled read, modify, verify, and recover operations via six session control tools.

Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.

A server based on the MCP framework that provides remote server management capabilities through SSH, supporting features like connection pooling, file transfers, and remote command execution.

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

A comprehensive MCP server for developers providing file operations, shell execution, git integration, and smart caching to enhance AI-assisted development.

The m2m-mcp-server-ssh-client provides a unified MCP server interface, securely connecting via SSH to the m2m-mcp-server-ssh-server back-end which aggregates MCP servers. This setup offers secure, single-point access to diverse remote tools using robust SSH key-based authentication.

Integrates 7 security tools (nmap, nuclei, dirsearch, sqlmap, hydra, Acunetix, Metasploit) via MCP protocol for AI-assisted penetration testing with enterprise-grade safety features.

Enables a local Windows developer agent to perform atomic filesystem operations, validated AST-based code edits, PowerShell/CMD process execution, and durable SQLite-backed background jobs with system diagnostics. It can run either as a loopback Streamable HTTP server or over an outbound encrypted OpenAI Secure MCP Tunnel with a local supervisor control panel.

A Python framework that enables secure hardware control through the Model Context Protocol, allowing AI agents and automation systems to interact with physical devices across multiple platforms.