Unreal Engine 5.8 introduces experimental MCP server support, letting AI assistants build games from inside the editor

Kraken has released an open-source CLI and MCP server that lets developers connect trading commands to AI tools, with live-order security caveats.

An MIT study found AI assistants improved misinformation detection in the moment, but appeared to weaken users' ability to spot falsehoods on their own.

EU antitrust regulators have ordered Meta to give rival AI chatbots free access to WhatsApp during an active competition probe. The European Commission said Meta must maintain access while Brussels investigates its policy toward competing AI assistants. The interim measure…

I got tired of copying files into an AI chat just to get feedback. So I built a pure Python MCP server that gives AI tools direct access to my local project—no frameworks, no dependencies. It runs over stdio for local use and switches to HTTP/SSE for concurrent clients with a single flag. The result: 5 clients, under 50ms, and a design that stays simple without sacrificing capability. The post My AI Couldn’t See My Files — I Built a Zero-Dependency MCP Server appeared first on Towards Data Science.

MoonPay's new desktop app connects AI assistants to crypto wallets and blockchain services through a graphical interface.

There’s no denying the excitement around Model Context Protocol (MCP), an open protocol for connecting AI assistants with external data, tools, and APIs. Since its debut by Anthropic in late 2024, thousands of MCP servers have emerged for devops, cloud, and beyond. Now that developers have integrated MCP servers into applications, and they have been battle-tested, usage patterns are emerging. For instance, supplying better context for AI is the most commonly cited primary value of using MCP, according to Zuplo’s State of MCP report released in early 2026. The Zuplo report also found that 63% of MCP users adopt MCP servers for accessing data sources such as documentation or knowledge bases. In software development, context engineering is the act of supplying AI coding agents with relevant data and capabilities to improve the accuracy and relevance of their outputs. It also involves optimizing the breadth of information to guide efficient processing. Such context can include coding style

Google launched Gemini Intelligence, a feature suite that aims to turn Android devices into proactive AI assistants.

New research suggests that reliance on AI assistants can have a negative impact on people’s ability to think and problem solve.