Updated: GAS Library - MCPApp
MCPApp was updated to v2.0.6
-
v2.0.6 (August 1, 2025)
- “prompts/get” method was updated.
You can see the detail information here https://github.com/tanaikech/MCPApp
v2.0.6 (August 1, 2025)
You can see the detail information here https://github.com/tanaikech/MCPApp
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.
v1.0.12 (July 31, 2025)
prompts/list was called even when prompts wasn’t included in capabilities. This resulted in the error Error discovering prompts from gas_web_apps: MCP error -32001: Request timed out when prompts wasn’t returned for prompts/list. To resolve this, I updated ToolsForMCPServer to return an empty array for prompts, which eliminated the error. Consequently, with this update in v1.0.12, you can now set custom prompts and resources.You can see the detailed information here https://github.com/tanaikech/ToolsForMCPServer
v2.0.5 (July 31, 2025)
You can see the detail information here https://github.com/tanaikech/MCPApp
This report demonstrates managing Google Calendar from the command line using Gemini CLI and an MCP server, enabling powerful, scriptable automation for your schedule.
Following up on my previous report, “Next-Level Data Automation: Gemini CLI, Google Sheets, and MCP,” I’m excited to present the next installment in this series. My earlier report, published on Medium, detailed an innovative approach to managing Google Sheets through the powerful combination of Gemini CLI and an MCP server. Ref
v1.0.10 (July 26, 2025)
You can see the detailed information here https://github.com/tanaikech/ToolsForMCPServer
v1.0.9 (July 24, 2025)
You can see the detailed information here https://github.com/tanaikech/ToolsForMCPServer
v1.0.8 (July 23, 2025)
oneOf has been removed from the schema of each tool.manage_google_docs_using_docs_api, manage_google_sheets_using_sheets_api, and manage_google_slides_using_slides_api, please use your API key for the Gemini API.You can see the detailed information here https://github.com/tanaikech/ToolsForMCPServer
Effortlessly generate API request bodies from natural language commands. This guide demonstrates using Gemini and Google Apps Script to streamline automation and accelerate development for Google Workspace APIs and beyond.
In a recent article, “Managing Google Docs, Sheets, and Slides by Natural Language with Gemini CLI and MCP,” I showcased a powerful method for dynamically creating API request bodies using natural language. This approach, utilizing the Gemini CLI and a My Custom Proxy (MCP) server, allows users to manage Google Workspace applications with simple, human-readable commands. The core concept is that generating API request bodies directly from natural language within a script can dramatically streamline automation and development.
v2.0.13 (July 22, 2025)
responseJsonSchema was added.models/gemini-2.5-flash-preview-04-17 to models/gemini-2.5-flash.You can see the detail information here https://github.com/tanaikech/GeminiWithFiles
Registered Application Name: Workspace & Gemini AI Orchestration Engine
This web page serves as the official homepage and privacy compliance interface for the application "Workspace & Gemini AI Orchestration Engine". This specialized developer utility is designed to research, benchmark, and optimize advanced integrations between Google Workspace services, the Google Apps Script API, and Gemini AI models (via Google Vertex AI / Gemini API endpoints).
The application facilitates automated multi-agent scaffolding, programmatic script deployment, project resource management, and structural analysis of Google Apps Script projects. It allows developers and autonomous AI agents (operating via Model Context Protocol / MCP) to securely evaluate execution performance, implement high-performance batch requests, and test agent-to-agent (A2A) workflows within a controlled and structured environment.
Our application explicitly requests access to specific Google user accounts through OAuth scopes required strictly for interacting with the Google Apps Script API and Google Workspace endpoints. This access is utilized solely to execute user-initiated or agent-orchestrated programmatic operations—such as creating, modifying, deploying, or benchmarking script projects and executing automated workflows. No background automated extraction occurs without explicit session initiation.
Adhering to a strict Zero-Retention Model, this application does not store, log, or persist any personal data, OAuth tokens, script source codes, or Google account configurations on any external server, database, or persistent storage medium. All data processing and API responses are handled entirely in-memory or securely on the client side within the active session context, ensuring complete cryptographic transient isolation.
We maintain absolute data privacy. No data accessed via Google OAuth scopes is shared, sold, rented, or transferred to third-party entities, advertising networks, or data brokers. All data transmissions are strictly point-to-point, encrypted in transit using industry-standard protocols, and limited entirely to the direct channel between the execution environment and Google's official API gateways.
For inquiries regarding this developer application, technical benchmarks, or verification compliance, please refer to the official documentation and repositories linked on this homepage (tanaikech.github.io).