"How to Work with Excel and Word Documents" matching MCP servers:

A local MCP server that connects Claude Code to your work environment through auditable tools for file operations, API calls, and command execution, with safety gates and configuration.

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

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.

Memory bank with Server as SSH support for central knowledge base

A local MCP bridge that lets ChatGPT chat mode operate the user's own computer, running project, file, and shell tasks through a local executor and returning progress and results to the conversation. It also coordinates Codex sessions (persistent or one-off) and other agent CLIs as sub-agents.

MCP server that enables AI clients to orchestrate multi-node LAN agents, with tools for remote command execution, file transfer, task delegation, and cross-node collaboration.

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.

Enables a Claude Code cloud session to run shell commands inside a chroot jail on your own computer and to call the MCP servers already installed there, with every request authenticated and relayed over a Cloudflare quick tunnel so no router port is opened and no SSH key or tunnel is ever handed to the cloud VM.

A demo MCP server that enables users to interact with various tools through natural language, including note management, weather queries, calculations, file operations, and shell commands. Uses Ollama for intent detection and structured command parsing from free text input.

Enables remote server control via SSH through Claude, supporting command execution, file transfers, and multi-server management with both standard and streamable HTTP protocols.

Enables AI clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.

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

Enables AI-assisted development tools like Cursor, Cline, and Windsurf to request user confirmation before acting, running shell commands and displaying their output inside a Qt feedback window that returns user notes and logs to the model. This human-in-the-loop loop lets the assistant consolidate many speculative tool calls into a single feedback-aware request, saving API usage and improving accuracy.

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.

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

Enables MCP clients to securely work with local files, directories, searches, terminal sessions, and processes on paired computers via outbound connections, without exposing inbound ports.

Runs git-bash (MSYS2) commands for AI agents on Windows from outside the agent's sandbox, so pipelines, command substitution, and subprocesses work. Exposes exec, bash_info, doctor, and policy tools with timeouts, output spilling, concurrency limits, capability-based command gating, and JSONL auditing.