AI’ into more and more places, Anthropic’s Model Context Protocol (MCP) has been adopted as the standard to connect LLMs ...

What if the next generation of AI systems could not only understand context but also act on it in real time? Imagine a world where large language models (LLMs) seamlessly interact with external tools, ...

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 ...

Artificial intelligence has gone beyond being associated with highly complex algorithms or large amounts of data. Currently, the greatest complexity in artificial intelligence rests in the way answers ...

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 ...

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 ...

AI agents and agentic workflows are the current buzzwords among developers and technical decision makers. While they certainly deserve the community's and ecosystem's attention, there is less emphasis ...

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 ...

Ashay Satav is a Product leader at eBay, specializing in products in AI, APIs and platform space across Fintech, SaaS and e-commerce. Model context protocol (MCP) has been the talk of the town lately, ...

The Model Context Protocol (MCP) for agentic AI has gained much traction since being introduced by Anthropic last November, and now it has a C# SDK. The MCP is a standard for integrating large ...

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 ...