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Announcing the Colab MCP Server: Connect Any AI Agent to Google Colab

When you’re prototyping locally with AI agents like Gemini CLI, Claude Code, or your own agent, thei...

Get ready for Google I/O 2026

Google I/O returns May 19-20. Watch the livestreams for updates on Android, AI, Chrome, and Cloud. Registration is open on the Google I/O website.

Tailor Gemini CLI to your workflow with hooks

New Gemini CLI hooks (v0.26.0+) let you tailor the agentic loop. Add context, enforce policies, and block secrets with custom scripts that run at predefined points in your workflow.

Beyond the Chatbot: A Blueprint for Trustable AI

At Thunderhill Raceway Park, a team of Google Developer Experts (GDEs) put a new "Trustable AI Framework" to the test. Here is how they used GCP, Gemini and Antigravity to turn high-velocity racing into a masterclass for agentic architecture.

Easy FunctionGemma finetuning with Tunix on Google TPUs

Finetuning the FunctionGemma model is made fast and easy using the lightweight JAX-based Tunix library on Google TPUs, a process demonstrated here using LoRA for supervised finetuning. This approach delivers significant accuracy improvements with high TPU efficiency, culminating in a model ready for deployment.

Introducing the Developer Knowledge API and MCP Server

Google is launching the Developer Knowledge API and MCP Server in public preview. This new toolset provides a canonical, machine-readable way for AI assistants and agentic platforms to search and retrieve up-to-date documentation across Firebase, Google Cloud, Android, and more. By using the official MCP server, developers can connect tools directly to Google’s documentation corpus, ensuring that AI-generated code and guidance are based on authoritative, real-time context.

Access public data insights faster: Data Commons MCP is now hosted on Google Cloud

Data Commons has launched a free, hosted Model Context Protocol (MCP) service on Google Cloud Platform, eliminating the need for users to manage complex local server installations. This update simplifies connecting AI agents and the Gemini CLI to Data Commons, allowing Google to handle security, updates, and resource management while users query data natively.

Making Gemini CLI extensions easier to use

To simplify the user experience and prevent startup failures, the Gemini CLI has introduced structured extension settings that eliminate the need for manual environment variable configuration. This update enables extensions to automatically prompt users for required details during installation and securely stores sensitive information, such as API keys, directly in the system keychain. Users can now easily manage and override these configurations globally or per project using the new Gemini extensions config command.

Conductor Update: Introducing Automated Reviews

Conductor for the Gemini CLI has introduced a new Automated Review feature designed to verify the quality and accuracy of AI-generated code. This update addresses the challenge of validating agentic development by automatically checking implementations against original plans, enforcing style guides, and identifying security risks or bugs. by incorporating test-suite validation and providing actionable reports, Conductor helps developers ensure that their AI agents deliver safe, predictable, and architecturally sound code before it is finalized.

Turn creative prompts into interactive XR experiences with Gemini

The Android XR team is using Gemini's Canvas feature to make creating immersive extended reality (XR) experiences more accessible. This allows developers to rapidly prototype interactive 3D environments and models on a Samsung Galaxy XR headset using simple creative prompts.