This article introduces a method for integrating Google's Gemini CLI and GitHub's Copilot CLI using the Model Context Protocol (MCP). By configuring one CLI as an MCP server, the other can invoke it from a prompt, enabling a powerful, collaborative interaction between the two AI assistants for enhanced development workflows.

This article introduces a method for securely executing AI-generated Google Apps Script. By implementing a "fake-sandbox" using the gas-fakes library as an MCP server, users can empower the Gemini CLI to safely automate Google Workspace tasks with granular, file-specific permissions, avoiding significant security risks.

This guide explores a powerful workflow for generating articles and other content by integrating Gemini CLI, a Model Context Protocol (MCP) server, and Visual Studio Code (VSCode). Discover how to leverage this combination for efficient, context-aware content creation, modification, and distribution, complete with practical examples and prompts.

This article introduces a Node.js wrapper that dramatically reduces the startup time for the Gemini CLI when used with MCP servers built on Google Apps Script. This optimization enhances user experience by accelerating the initialization process, achieving a speed boost of approximately 15 times.

This article demonstrates integrating Google Maps with natural language using the Gemini CLI and an MCP server. This powerful combination allows users to automate complex location-based tasks, such as route planning and information retrieval, through simple, intuitive text-based prompts.

Generating Google Apps Script (GAS) with Gemini CLI from natural language introduces security risks due to broad permissions. This report investigates a "Fake-Sandbox" using the gas-fakes library, translating GAS calls into granularly-scoped API requests to securely execute scripts created from user prompts.

This report introduces a powerful method for automating Google Analytics tasks using the Gemini CLI and a custom MCP (Model Context Protocol) server built with Google Apps Script. This integration enables streamlined web page analysis through simple natural language commands, simplifying authorization and complex data retrieval workflows.

This document demonstrates a transformative method for unifying Google Workspace applications by using natural language. Through the integration of the Gemini CLI with MCP, this approach empowers users to intuitively manage Google Drive, Gmail, Google Calendar, Drive Activity, and Google People. Complex tasks and collaborative workflows are streamlined into simple, conversational text commands.

Automate Google Classroom management with natural language. This guide details using the Gemini CLI and an MCP server to streamline creating classes, managing assignments, and interacting with students.

This report provides a comprehensive overview of how to utilize prompts within the Gemini Command-Line Interface (CLI). Leveraging a Google Apps Script MCP server, we will explore practical examples, including roadmap generation, real-time weather inquiries, and Google Drive file searches. This enhanced document offers more in-depth explanations and a broader context to empower users in their understanding and application of these powerful features.

The Model Context Protocol (MCP) establishes a standardized framework for servers to offer clients predefined, structured prompt templates. These user-controllable prompts, customizable with arguments, are engineered to streamline interactions with large language models. The Gemini CLI, starting with version v0.1.15, integrates support for these prompts, significantly expanding its capabilities.