Model Context Protocol Explained in 3 Levels of Difficulty

The post Google Expands Gemini API Managed Agents With Key Updates appeared on BitcoinEthereumNews.com. James Ding Jul 07, 2026 20:08 Google enhances Gemini API Managed Agents with background tasks, remote MCP integration, and more, boosting AI development capabilities. Google has rolled out significant updates to its Managed Agents in the Gemini API, designed to enhance developer capabilities for building production-ready AI agents. Announced on July 7, 2026, these additions include long-running background task support, remote Model Context Protocol (MCP) server integration, custom function execution, and streamlined credential management. These updates build on Google’s broader push into agentic AI, following the debut of Managed Agents during Google I/O in May 2026. Managed Agents enable developers to create isolated cloud-based Linux environments that handle reasoning, code execution, and web browsing within a single API call. The Gemini Interactions API, which po

Microsoft has fitted the June 2026 update to Visual Studio IDE with a GitHub Copilot usage window that gives a clearer view of where a user stands against the GitHub’s new usage-based model. The update also adds trust validation for Model Context Protocol (MCP) servers. GitHub Copilot usage now is calculated based on token consumption rather than by request, as part of GitHub’s new usage-based billing model, Microsoft said on June 30. The refreshed usage window in Visual Studio gives a clearer view of the stance against that model, with real-time updates as the developer works. This can be opened by selecting Copilot Usage from the Copilot badge menu. GitHub Copilot switched to usage-based billing on June 1. Also with the June update, Visual Studio now validates MCP server trust in two places during startup. Before the MCP server process starts, the current configuration is compared against a previously trusted baseline. After it starts, the fingerprint of its tools, prompts, resourc

Why it matters: Learn how vendor lock-in agentic AI platforms trap enterprises and how open standards like MCP and A2A cut switching costs of 19 to 34 percent.

The enhanced efficiency and capacity of 3D NAND flash memory could drive down costs and fuel innovation in data storage and AI applications. The post Kioxia and Sandisk begin production of 10th-generation 3D NAND flash memory in Japan appeared first on Crypto Briefing.

SnapLogic has released MCP Builder, a template-based tool designed to help organizations operationalize AI faster by turning existing integration pipelines into agent-ready Model Context Protocol (MCP) servers. Announced July 1 and generally available in the MCP Server workflow of the SnapLogic platform, MCP Builder generates MCP servers from existing integrations, OpenAPI specifications, and API management services, SnapLogic said. Organizations can publish MCP tools without rebuilding workflows, writing code, or manually constructing MCP implementations, resulting in faster deployment and greater consistency, according to the company. SnapLogic said MCP Builder makes it easier to create MCP Servers, connecting AI agents to trusted enterprise systems and workflows. Unlike DIY MCP approaches, SnapLogic accelerates MCP adoption by turning existing deterministic pipelines into governed MCP tools through a one-step creation experience, while providing enterprise connectivity, identity pr

X has unveiled a hosted Model Context Protocol server, giving AI tools such as Claude, Cursor, and Grok Build direct access to the platform through a user’s own account permissions, without requiring developers to build and maintain their own integration infrastructure. The Model Context Protocol is an open standard that defines how AI models communicate […]

Microsoft has introduced the Microsoft Binlog MCP Server, which gives AI assistants like GitHub Copilot direct access to MSBuild (.binlog) files. The Model Context Protocol server enables AI-powered build investigation through natural language conversation, Microsoft said. Introduced June 17 and currently in a preview stage, the Microsoft Binlog MCP Server parses .binlog files and exposes 15 specialized tools that enable AI-driven diagnosis, property tracing, performance analysis, and build comparison. Microsoft said that AI assistants gain the ability to do the following: Investigate build failures by querying errors, warnings, and full project/target/task context Trace property origins to understand where a property got its value Analyze performance bottlenecks by identifying the slowest projects, targets, and tasks Compare two builds to spot differences in packages and properties Read embedded source files captured during the build Instead of manually scrolling through the MSBuild

The partnership could revolutionize financial analysis, enabling more accurate, data-driven decisions and fostering innovation in AI applications. The post FactSet partners with Google Cloud to enhance financial intelligence with AI appeared first on Crypto Briefing.