Gists
Abstract 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.
Introduction 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.
Gists
Abstract 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.
Introduction Recently, the Model Context Protocol (MCP) has emerged as a standard protocol for connecting AI applications with third-party systems and data sources.
Gists
Abstract The report details a novel Gemini API method to analyze big data beyond AI context window limits, which was validated with Stack Overflow data for insights into Google Apps Script’s potential.
Introduction Generative AI models face significant limitations when processing massive datasets, primarily due to the constraints imposed by their fixed context windows. Current methods thus struggle to analyze the entirety of big data within a single API call, preventing comprehensive analysis.
Gists
Abstract 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.
Introduction The rapid advancement and widespread adoption of generative AI have been remarkable. High expectations are placed on these technologies, particularly regarding processing speed and the capacity to handle vast amounts of data. While AI processing speed continues to increase with technological progress, effectively managing and analyzing truly large datasets presents significant challenges.
GeminiWithFiles was updated to v2.0.6 v2.0.6 (April 23, 2025)
A new method countTokens was added. Ref When this method is used, you can count tokens of the request. This pull request was reflected. Ref You can see the detail information here https://github.com/tanaikech/GeminiWithFiles