This report details the Agent2Agent (A2A) network built with Google Apps Script's Web Apps. It facilitates communication between diverse AI agents, overcoming platform limitations. Key improvements include parallel task execution with asynchronous processes and enhanced security through secure access token handling and user-specific Web App availability, demonstrating a robust and secure A2A implementation.
Kanshi TANAIKE tanaikech
Exploring Agent2Agent (A2A) protocol implementation in Google Apps Script seamlessly allows AI agents to access Google Workspace data and functions. This could enable complex workflows and automation, overcoming platform silos for integrated AI applications.
This report details transferring image data via Model Context Protocol (MCP) from Google Apps Script server to a Python/Gemini client, extending capabilities for multimodal applications beyond text.
Following up on my previous report, "Building Model Context Protocol (MCP) Server with Google Apps Script" (Ref), which detailed the transfer of text data between the MCP server and client, this new report focuses on extending the protocol to handle image data. It introduces a practical method for transferring image data efficiently from the Google Apps Script-based MCP server to an MCP client. In this implementation, the MCP client was built using Python and integrated with the Gemini model, allowing for the processing and utilization of the transferred image data alongside text, the
This text introduces the Model Context Protocol (MCP) for standardizing AI interaction with external systems. It explores the potential of using Google Apps Script (GAS) to host an MCP server, leveraging GAS's integration with Google Workspace for data access. A sample script demonstrates feasibility, highlighting the current absence of an official GAS SDK. The work aims to foster understanding and encourage SDK development.
Generative AI faces limits in processing massive datasets due to context windows. Current methods can't analyze entire data lakes. This report presents a Gemini API approach for comprehensive big data analysis beyond typical model limits.
Learn how Gemini AI and Google Apps Script automate Google Slides generation. A developed application demonstrates this synergy, streamlining initial presentation drafting and showcasing AI's automation potential within Google Workspace.
The field of AI, particularly large language models like Google's Gemini, is advancing rapidly. A powerful application of this technology involves integrating Gemini with Google Apps Script. Google Apps Script provides a seamless way to automate tasks across Google Workspace by natively handling authorization and interaction with services like Google Docs, Google Sheets, and Google Slides. By combining Gemini's generative capabilities with Apps Script, sophisticated automations become accessible.
Gemini 2.5 Pro Experimental enabled automated cargo ship stowage planning via prompt engineering, overcoming prior model limitations. This eliminates the need for complex algorithms, demonstrating AI's potential in logistics.
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