Chances are, unless you're already deep into AI programming, you've never heard of Model Context Protocol (MCP). But, trust me, you will. MCP is rapidly emerging as a foundational standard for the ...

The Model Context Protocol (MCP) is redefining how artificial intelligence (AI) systems interact with external tools and services. By addressing the inherent limitations of large language models (LLMs ...

AI needs contextual interconnection to work. Model Context Protocol is an open standard developed by the maverick artificial intelligence startup Anthropic. It is designed to allow AI agents to access ...

Microsoft Corp. believes we’re headed toward a future where artificial intelligence-powered agents will become pervasive in enterprise computing environments, so today it’s making it easier for those ...

What if the way AI agents interact with tools and resources could be as seamless as browsing the web? Imagine a world where developers no longer wrestle with custom-built adapters or fragmented ...

The Model Context Protocol (MCP) is an open source framework that aims to provide a standard way for AI systems, like large language models (LLMs), to interact with other tools, computing services, ...

Apple has embraced agentic AI for developers, introducing direct support in Xcode 26.3 for both Anthropic’s Claude Agent and OpenAI’s Codex and making vibe coding now a platform feature for iPhone, ...

While the current AI boom was sparked by the launch of OpenAI’s ChatGPT in late 2022, it wasn’t until late 2024 that its true power could be recognized, when Anthropic unveiled the Model Context ...

Released late last year by AI firm Anthropic, model context protocol (MCP) is an open standard designed to standardize the way AI systems, particularly large language models (LLMs), integrate and ...

MCP certification is a hot topic in AI hiring. Here’s what courses are available now, when official certification might arrive, and why it may not solve every problem. The Model Context Protocol (MCP) ...

AI innovation today is moving faster than ever before, with leaps and bounds being made in the field on what seems like a weekly basis. Further to innovation that is directly related to or produced by ...

As enterprises push AI into production, they're encountering a fundamental constraint: general-purpose models lack the real-time operational context that enterprise decisions require.