An open standard that enables AI models to interact with tools, memory, and data in a structured, auditable way.
As AI development accelerates, organizations are under increasing pressure to move models from prototype to production securely and with scalability.
The increasingly popular Model Context Protocol lets AI models access applications, but studies show that the best generative AI bots struggle with planning across a variety of tasks.
Imagine you’ve trained or fine‑tuned a chatbot or an LLM, and it can chat comfortably without any serious hiccups. You feed it a prompt and it responds. However, it’s stuck in a bubble: It only knows ...
Imagine a world where your AI tools don’t just work for you but work with each other—seamlessly, intelligently, and without the frustration of endless custom integrations. This isn’t a distant dream; ...
For years, APIs have powered everything from SaaS dashboards to mobile apps. Now, a new contender—Model Context Protocol, or ...
Anthropic’s Model Context Protocol (MCP) is an open standard designed to enable secure, two-way communication between tools and data sources. Its flexibility and efficiency make it a valuable resource ...
More processors on SoCs means more sophisticated cache control. This article describes formal techniques for verifying cache coherency for the ARM AMBA AXI Coherency Extensions (ACE) protocol. Fig 1.
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