Google Expands Gemini Enterprise Agent Platform with Remote MCP Server

CloudBees, a continuous integration/delivery (CI/CD) company, is shifting its focus to become an AI-first organization under new CEO Mo Plassnig. This strategic change addresses the increasing volume of machine-generated code and the challenges enterprises face in managing it.

Google Cloud introduced a preview of the Google Cloud CLI remote MCP server, enabling AI agents to access gcloud and bq command-line operations. This server provides a standardized way for agents to manage Google Cloud infrastructure and BigQuery workflows, addressing challenges in agent interaction with backend systems.

Google Cloud has expanded its Gemini Enterprise ecosystem with new partner-built security agents and AI defenses. These integrations allow enterprises to orchestrate multi-step security workflows and leverage AI-powered capabilities from a unified interface, addressing the increasing use of AI in cyberattacks.

Google Earth Engine launched "Ask," a new feature integrating Gemini AI capabilities directly into its Code Editor. This allows users to write, debug, understand, and optimize geospatial queries using AI, accelerating the development of geospatial insights.

Latin American small and medium-sized businesses (SMBs) are increasingly adopting Google Cloud AI tools, with an 8x year-over-year growth across the region and 9x growth in Brazil. These businesses are using Gemini Enterprise and other Google Cloud AI offerings to automate tasks, improve customer support, and analyze data.

Google has released Gemini CLI 0.61.0, which now requires explicit user confirmation before the agent can edit build configuration files, run build or test commands after such edits, or execute shell commands derived from untrusted external content. This update enhances security by reintroducing human oversight at critical points where an autonomous coding agent could be exploited by attackers.

Google Cloud states that startups are increasingly choosing its platform for AI development, citing its comprehensive stack as a key driver. The company highlights the growth of Gemini Enterprise and the strong price-performance of Gemini models for various AI workloads.

Google is promoting its "Intelligent Endpoints" strategy, integrating AI into Chrome and other enterprise products to automate tasks and improve productivity. This initiative aims to reduce manual work for employees by enabling agentic workflows directly within the browser and through a new enterprise Skills library for Gemini in Chrome.

Google Cloud launched a new plugin for AI coding agents, designed to bundle skills and tools for Google Cloud interactions. This plugin addresses the challenge of managing individual AI agent skills by packaging related capabilities into cohesive, installable units, making agents more effective for Google Cloud users.

Google has been recognized as a Leader in Gartner's first 2026 Magic Quadrant for Enterprise AI Assistants, based on its Completeness of Vision and Ability to Execute. This placement highlights Google's Gemini Enterprise platform, which aims to provide a unified and secure AI solution for businesses.

Google Cloud introduced the Antigravity SDK, providing the runtime engine from Antigravity 2.0 and Antigravity CLI for building custom agent hubs. This SDK includes declarative safety policies, real-time telemetry, and stateful multi-turn persistence, allowing developers to create centralized systems for monitoring and managing LLM workloads.

Google Cloud has been named a Leader in the 2026 Gartner Magic Quadrant for Strategic Cloud Platform Services. This recognition highlights Google Cloud's integrated technology stack, dynamic infrastructure, and focus on digital sovereignty, which are presented as key differentiators for customers building and scaling demanding workloads.

Google has launched the Fairwind Program, offering select Google Cloud customers, government agencies, and cybersecurity partners early access to advanced AI cyber defense capabilities. The program utilizes Gemini 3.8 Flash Cyber and CodeMender to autonomously find, verify, and fix software vulnerabilities, aiming to provide rapid patch generation and enhance security for critical infrastructure and public services.

Google has launched agentic video understanding across its Gemini 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite models. This new capability improves video analysis accuracy while significantly reducing token usage and costs, particularly for long-form video content.

Pythian developed an AI Operating Model after deploying Google Cloud's Gemini Enterprise internally, aiming to achieve significant ROI from enterprise AI initiatives. The model addresses common failures in enterprise AI adoption by integrating strategy, execution, and operations into a continuous framework, which Pythian claims led to a 3x increase in user engagement and an 80% reduction in database incident resolution times.

Google Cloud has launched AI-powered Database Operations Agents, including an Onboarding Agent for database setup and an Observability Agent for troubleshooting and performance optimization. These agents integrate with Gemini Cloud Assist and support various Google Cloud database services, aiming to automate and simplify database lifecycle management for developers and engineers.

Google Cloud introduced Gemini Enterprise for Legal, an agentic AI solution designed to automate legal tasks such as contract review and document drafting. This release, alongside Gemini Enterprise for Financial Services, indicates a trend towards specialized AI solutions for professional domains, highlighting a competitive shift in enterprise AI development.

Google has launched expanded billing flexibility and cost management tools for AI agent workloads within Gemini Enterprise and developer tools like Google Antigravity and Android Studio. These updates aim to provide businesses with clearer visibility and proactive controls over AI spending, offering options like pay-as-you-go, consolidated developer access, and Flexible Savings Plans.

Google Developer Relations has launched "Agent Valley," a free, five-week live learning series designed to teach participants how to build AI agent systems from basic concepts. The program aims to make AI agent development accessible to beginners through hands-on exercises in a virtual world environment.

Google Cloud has launched Gemini Enterprise for Legal, a new AI solution designed specifically for the legal industry. This offering integrates specialized AI capabilities with existing legal systems to handle tasks like contract review and legal research, addressing the need for AI that adheres to legal industry standards and data security requirements.

Google Cloud has introduced Gemini Enterprise for Financial Services, an AI solution designed to integrate agentic AI into capital markets and corporate banking workflows. This offering aims to provide financial institutions with specialized AI capabilities, secure data integration, and auditable research agents, addressing the industry's need for precision and security in AI applications.

Google Antigravity, a coding agent tool, is now available for enterprise customers as part of eligible Gemini Enterprise app subscriptions, including administrative and spend controls. This update allows developers to use Antigravity within their preferred IDEs, such as VS Code, and provides organizations with consolidated governance over AI developer tools.

Google Cloud AI published a guide for startups on transitioning AI prototypes to production, addressing common challenges like API key management, platform migration, and quota limitations. The guide provides 10 questions across onboarding, scaling, and governance phases to help startups avoid typical failure modes when deploying AI solutions.

Looker's semantic layer now integrates with Gemini Enterprise, providing a governed foundation for structured data within Google's AI chat interface. This integration allows Gemini Enterprise users to query both structured and unstructured data in natural language, aiming to reduce AI hallucinations and improve data consistency.

Google has been named a Leader in The Forrester Wave™: AI Platforms, Q3 2026 report, receiving the highest score in the Strategy category. This recognition highlights Google's Gemini Enterprise platform, which unifies enterprise data, model capabilities, developer tooling, and IT operations for building and deploying AI agents.

Google Cloud detailed its strategies for identifying and mitigating security threats, including AI workload exploitation, cryptocurrency mining, credential exfiltration, and account takeovers. The company uses infrastructure telemetry and active monitoring to protect customer data and systems.

Google Cloud is providing free educational resources, including hands-on labs and courses, to help developers build and deploy AI agents using the Gemini Enterprise Agent Ready (GEAR) framework. These resources cover topics from foundational understanding to orchestrating multi-agent workflows and earning skill badges.

Google Cloud announced two new AI-powered database agents at Google Cloud Next ‘26: the Database Onboarding Agent for setup and configuration, and the Database Observability Agent for monitoring and troubleshooting. These agents automate database lifecycle management tasks, aiming to reduce manual effort and improve operational efficiency for database users.

Pillar Security identified an agent-to-agent attack method within Google's Agent Development Kit (ADK) for Python, which could expose secrets and enable pull request tampering. This vulnerability allowed manipulation of low-privileged AI agents to gain access to restricted capabilities of high-privileged agents, posing a supply chain risk.

Google Cloud announced the general availability of Cortex Framework version 7, which provides purpose-built data product accelerators for SAP, deployed in BigQuery and Knowledge Catalog. This release modernizes data architecture to support AI agents by transforming SAP transactional records into AI-ready data products, simplifying orchestration, and reducing infrastructure overhead.

Google provided insight into the development process and quality control mechanisms for Google Agent Skills, which encode Google Cloud domain knowledge into structured instructions for AI coding agents. The company outlined how it maintains consistency and quality as more teams contribute skills, emphasizing a standardized repository layout and preference for remote Model Context Protocol (MCP) tools.

Google Cloud has announced the general availability of Managed Lustre and C4N network and storage optimized VMs. These updates provide enhanced high-performance storage and improved network bandwidth for AI and data-intensive workloads on Google Cloud.

Gemini Robotics 2 has been released, providing robots with intelligent whole-body control, advanced dexterity, and multi-robot collaboration capabilities. This development allows robots to perform complex tasks and adapt to new robotic bodies more efficiently, addressing limitations in traditional pre-programmed or teleoperated systems.

Gemini Robotics ER 2, an "embodied reasoning" model for robotics, has been launched, offering improved video understanding, task orchestration, and multi-robot collaboration capabilities. This update allows robots to better track progress, adapt to changes, and work together on complex tasks, advancing physical AI agentic capabilities.

A tutorial details how to use Agents CLI to manage the entire development lifecycle of AI agents within Gemini Enterprise, from setup to deployment and evaluation. This approach aims to simplify the transition of AI projects from prototype to production by consolidating tools and processes.

Google Cloud has made several capabilities of its Gemini Enterprise Agent Platform, including Agent Runtime and Agent Identity, generally available. This update allows businesses to automate long-running agentic workflows with improved memory and extended execution times, and introduces CodeMender for automated code remediation.

Managed Agents in the Gemini API now default to Gemini 3.6 Flash, introduce environment hooks for tool call management, and offer explicit model selection. These updates provide developers with more control over agent behavior and model choice within the Gemini Interactions API.

Android Studio Quail 2 has redesigned Agent Mode to support multiple AI conversations, improving developer efficiency. It also integrates LeakCanary for enhanced memory leak detection and auto-synthesis of crash data to suggest fixes, streamlining the development process.

CodeMender, a managed code security agent, is now in preview, offering automated scanning and remediation of software vulnerabilities. This tool aids security teams in countering adversarial AI threats by significantly speeding up vulnerability management processes.

Google Cloud AI has introduced 13 hands-on demos for its Gemini Enterprise Agent Platform, designed to help users build and optimize AI agents. These demos exemplify different functionalities of the platform, including event-driven approval processes and integration with data sources.

Google Cloud's new Gemini Enterprise Agent Platform enables rapid AI model upgrades, reducing migration time from months to hours. This shift addresses longstanding issues faced by engineering teams in adapting to frequent model iterations.

A Russian-speaking hacker used Google's Gemini CLI AI tool as a hacking agent to control a botnet. This incident highlights vulnerabilities in open-source AI tools, potentially impacting cybersecurity across industries.

Google Cloud integrates BigQuery with the Gemini Enterprise app to aid administrators in managing large-scale deployments. This enhancement allows IT and security teams to analyze user behavior, quantify productivity, and execute compliance audits efficiently using pre-computed dashboards and detailed telemetry.

The Tambellini Group has recognized Gemini Enterprise for Education as a Commander in its StarChart for 2026 AI Agents for Administrative Efficiency. This designation highlights Gemini's integration of advanced AI capabilities, improving operational efficiency in higher education institutions.

Developers can now publish AI agents through Google Cloud Marketplace and Gemini Enterprise. The guide details steps for integration, organizational requirements, and agent architecture, emphasizing the significance of autonomy and multi-step workflows.

Gemini Enterprise Agent Platform has launched to assist IT leaders in building and deploying agents effectively. The platform centralizes the development process, enabling teams to manage risks such as data leaks and token exhaustion while fostering collaboration among various technical roles.

The Gemini API has added new features for Managed Agents, including support for background execution, remote MCP server integration, and custom function calling. These enhancements enable developers to build more efficient, production-ready AI agents by addressing previous limitations.

The Gemini Enterprise Agent Platform has introduced a remote Managed Control Plane (MCP) server to facilitate secure connection for external AI agents with Google Cloud resources. This development allows developers to create agents using their preferred IDEs while ensuring compliance and data protection.