Gmail Processing using MCP Network Powered by Google Apps Script

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Gmail Processing using MCP Network Powered by Google Apps Script

Abstract

This report details an MCP network using Google Apps Script for both server and client, enabling automated, secure Gmail processing to boost efficiency.

Introduction

Recently, I published a report titled “Building Model Context Protocol (MCP) Server with Google Apps Script,” which you can find here. In that initial report, I demonstrated the feasibility of creating an MCP server using Google Apps Script, with Claude Desktop serving as the client.

Text-To-Speech (TTS) using Gemini API with Google Apps Script

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Description

This script provides a simple example for generating Text-To-Speech (TTS) using the Gemini API within Google Apps Script. The Gemini API generates audio data in the audio/L16;codec=pcm;rate=24000 format, which is not directly playable. Since there’s no built-in method to convert this to a standard audio/wav format, this sample script includes a custom function to handle the conversion.

Limitations and Considerations

  • The provided convertL16ToWav_ function is specifically designed for the audio/L16;codec=pcm;rate=24000 MIME type. Using it with other audio formats will result in an error.
  • The script uses a hardcoded WAV header. This header assumes specific audio parameters (e.g., sample rate, bit depth, number of channels) that match the Gemini API’s output for this format. If the Gemini API’s output format changes, this header might need adjustment.

Sample Script

Before running, replace "###" with your actual Gemini API key in the myFunction.

Importance of Time Information in Gemini and Current Time Handling

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Importance of Time Information in Gemini and Current Time Handling

Abstract

This report investigates how Gemini handles current time information, particularly when using the Gemini API. We found that while the Gemini web interface knows the current time, the Gemini API does not inherently. Therefore, applications must explicitly provide current time information in API calls for accurate time-sensitive responses.

Introduction

The rapidly advancing field of generative AI is enabling increasingly complex tasks, particularly through the use of open protocols like the Model Context Protocol (MCP) and Agent2Agent (A2A) Protocol. These protocols facilitate sophisticated operations that often require accurate and dynamic information, including time-sensitive data. For instance, applications that manage schedules or coordinate events critically depend on precise time information.

Automating Straight to Smart Quote Conversion in Google Docs

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Automating Straight to Smart Quote Conversion in Google Docs

Abstract

For extensive Google Docs, manually converting straight to smart quotes is inefficient. This report offers an automated solution using Google Apps Script, saving time and effort.

Description

You might find yourself needing to convert straight quotes (both single and double) to smart quotes in Google Docs. For small documents with a limited number of quotes, this can be done manually with minimal effort. However, when dealing with extensive documents and numerous quotes, the manual process becomes time-consuming and inefficient. This report presents a solution to automate this conversion using Google Apps Script, significantly reducing the processing cost for larger projects.

Enabling Collaborative Agent Systems through Google Apps Script-based Agent2Agent (A2A) Network

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Enabling Collaborative Agent Systems through Google Apps Script-based Agent2Agent (A2A) Network

Abstract

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.

Introduction

This report details an updated implementation of Agent2Agent (A2A), an open protocol designed to enable communication and collaboration between diverse AI agents. The goal of A2A is to overcome limitations of isolated platforms, allowing AI agents to work together on complex tasks while maintaining their internal structures. I recently published a report titled “Building Agent2Agent (A2A) Server with Google Apps Script”. Ref This updated report focuses on successfully creating an A2A network using Google Apps Script’s Web Apps functionality.

Building Agent2Agent (A2A) Server with Google Apps Script

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Building Agent2Agent (A2A) Server with Google Apps Script

Abstract

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.

Introduction

Agent2Agent (A2A) is a proposed open protocol facilitating communication and collaboration among diverse AI agents, aiming to overcome platform silos and enable complex tasks while preserving agent opacity. This report examines the feasibility of implementing a core A2A server component using Google Apps Script within Google Workspace. Such an implementation could seamlessly allow AI agents to securely access and utilize data and functionalities across Google services like Docs, Sheets, and Gmail via a standardized protocol. This would enable sophisticated AI-powered workflows and automation directly linked to user data. A sample script demonstrates the technical potential despite the current lack of a dedicated Apps Script SDK for A2A. While acknowledging potential Apps Script limitations, such as execution time, this exploratory approach remains valuable for developing internal or user-centric AI applications and integrations within Google Workspace. A successful demonstration could potentially highlight the capabilities of Google Apps Script.