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 ...

Artificial intelligence is still rapidly evolving, though there remains one fundamental constraint on its effectiveness: the provision of authentic, immediate, and permissioned access to the relevant ...

There’s a quiet but profound transformation underway in how businesses interact with backend systems. It’s not a flashy app or piece of consumer technology - it’s happening at the infrastructure level ...

As organizations push AI systems into production, IT teams are asking how to make models more dependable, secure and useful in real-world workflows. One approach gaining traction is the Model Context ...

As AI agents begin operating across enterprise systems, MCP is emerging as the connective layer IT leaders can’t afford to ignore.

An interface between an AI language model and external sources such as a database. The Model Context Protocol server (MCP server) determines what the model can access. The MCP client, typically an AI ...

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; ...

Making inherently probabilistic and isolated large language models (LLMs) work in a context-aware, deterministic way to take real-world decisions and actions has proven to be a hard problem. As we ...

Artificial intelligence is progressing rapidly, but there is one issue that many people do not discuss enough: context. Even the most intelligent systems are not very effective when they lack a clear ...

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 ...