Tag: Google

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.

Introducing the Agent Development Kit (ADK) for TypeScript, an open-source framework for building complex, multi-agent AI systems with a code-first approach. Developers can define agent logic in TypeScript, applying traditional software development best practices (version control, testing). ADK offers end-to-end type safety, modularity, and deployment-agnostic functionality, leveraging the familiar TypeScript/JavaScript ecosystem.

ADK introduces **Context Engineering** to scale AI agents beyond large context windows. It treats context as a compiled view over a tiered, stateful system (**Session, Memory, Artifacts**). This architecture uses explicit processors for transformation, enables efficient compaction and caching, and allows for strict, scoped context handoffs in multi-agent workflows to ensure reliability and cost-effectiveness in production.

LiteRT and MediaTek are announcing the new LiteRT NeuroPilot Accelerator. This is a ground-up successor for the TFLite NeuroPilot delegate, bringing seamless deployment experience, state-of-the-art LLM support, and advanced performance to millions of devices worldwide.

Google Cloud enables end-to-end confidential applications, protecting sensitive data 'in-use' with hardware isolation. The solution combines Confidential Space (TEE/attestation), Oak Functions (private sandbox), and Oak Session (attested end-to-end encryption for scale). This framework anchors user trust in open-source components, proving confidentiality for sensitive workloads like proprietary GenAI models, even when running behind untrusted load balancers.

Gemini CLI's new automatic **Session Management** (v0.20.0+) saves your conversation history, tool outputs, and reasoning, providing project-specific context. Resume easily using the **Interactive Session Browser** (`/resume`) or command-line flags (`--resume`). This feature ensures you never lose your work state, capturing prompts, tool execution details, and usage stats. Customize history with cleanup policies in `settings.json`.

The new Gemini Interactions API enables stateful, multi-turn AI agent workflows, providing a single interface for raw models and the Gemini Deep Research Agent. It can be integrated with existing ADK systems as a superior inference engine with simplified state management, or used as a transparent remote A2A agent via InteractionsApiTransport, allowing seamless expansion of multi-agent systems with minimal refactoring.

A2UI is an open-source project for agent-driven, cross-platform, and generative UI. It provides a secure, declarative data format for agents to compose bespoke interfaces from a trusted component catalog, allowing for native styling and incremental updates. Designed for the multi-agent mesh (A2A), it offers a framework-agnostic solution to safely render remote agent UIs, with integrations in AG UI, Flutter's GenUI SDK, Opal, and Gemini Enterprise.

Learn how to build modular and reliable agentic applications using 8 effective multi-agent design patterns with the Agent Development Kit (ADK).

Conductor is a new Gemini CLI extension that promotes context-driven development. It shifts project context from chat logs to persistent Markdown files for formal specs and plans, ensuring AI agents adhere to project goals, style, and tech stack. This structured workflow is great for "brownfield" projects and teams, allowing for safe iteration and consistent code contributions while keeping the human developer in control.