Unlocking Google’s AI Ecosystem: The Ultimate Guide to Official MCP Servers
14 days ago 高效码农Unlocking Google’s AI Ecosystem: A Comprehensive Guide to Official Model Context Protocol (MCP) Servers Have you ever imagined your AI assistant directly fetching real-time map data for you, analyzing massive corporate datasets, or even managing your cloud-based Kubernetes clusters? This is becoming a reality through a technology called the Model Context Protocol. Google, as a core driver in the AI field, has built a vast and practical ecosystem of official MCP servers. This article will take you deep into each MCP tool provided by Google, from cloud-hosted services to open-source self-deployment options, revealing how you can seamlessly integrate these powerful …
Gemini 3 API Secrets: How Thinking Levels & Thought Signatures Boost AI Accuracy
1 months ago 高效码农Inside Gemini 3: How Thinking Levels, Thought Signatures and Media Controls Give You Production-Grade Reasoning Power This article answers one question: “What exactly changed in the Gemini API for Gemini 3, and how can I ship those features today without reading another 50-page doc?” What this guide covers (and why you should care) Gemini 3 is now the default engine behind Google AI Studio and the production Gemini API. The update ships three big levers you can pull—thinking depth, media resolution, and chain-of-thought signatures—plus cheaper web-grounding and native JSON output. Used together they let you tune cost, latency and accuracy …