"A guide to technical report writing" 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.

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.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

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

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.

An MCP server that enables AI assistants to execute shell commands and manage files on remote servers via SSH. It supports recursive directory uploads, archive extraction, and direct file creation from text content.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Enables MCP-compatible AI clients to connect to a Windows machine for file operations, PowerShell execution, Git inspection, task management, memory, and skills.

Enables AI agents to safely access and administer remote machines over SSH using existing OpenSSH config, with typed tools for running commands, reading and writing files, listing directories, and retrieving file metadata.

Enables reading, writing, editing, searching, running commands, transferring files, and using git on a remote Linux server over SSH via MCP tools.

Enables LLMs to securely SSH into remote servers, execute commands, and manage files via SFTP including listing, reading, writing, deleting, and renaming files.

Enables MCP-based communication with existing interactive terminal channels, such as shells or agent CLIs, by listing, reading, writing text, and sending control signals to tmux sessions without creating or managing them.

A Model Context Protocol server that provides programmatic access to the Windows terminal, enabling AI models to interact with the Windows command line through standardized tools for writing commands, reading output, and sending control signals.

MCP server that enables reading and writing macOS system preferences and application settings through the defaults system.

Enables ChatGPT to work with explicitly registered projects on a Windows device through a secure, self-hosted bridge.

Enables AI agents and humans to read and write a git-backed knowledge base through isolated sandbox sessions, with tools for creating and closing sessions, running shell commands, listing sessions, and retrieving guide documents.

Exposes a governed, OAuth-gated suite of 38 tools that let web AI clients work directly on your machine: reading, writing, and editing files, running whitelisted shell commands, searching, Git, SQLite, browser automation, DevTools debugging, background tasks, localhost/LAN fetches, clipboard, notifications, port management, and Postman control.

Enables AI agents to execute commands in a shared tmux session that is simultaneously visible to a human via a web-based terminal UI.

Enables an MCP client to run commands and inspect or edit files across multiple named SSH hosts through a single local connection, keeping terminal state between calls and reading long output a page at a time. It reports honest exit statuses and handles router CLIs and pagers such as --More-- without dumping whole logs into the conversation.