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 ...

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 ...

Can Model Context Protocol (MCP) make AI truly useful? Learn how this standard from Anthropic provides structured context, ...

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 ...

The Model Context Protocol just got its first official extension, and it changes what AI assistants can do. MCP Apps lets tools return interactive user interfaces—dashboards, forms, visualizations, ...

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 ...

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 ...

As enterprises push AI into production, they're encountering a fundamental constraint: general-purpose models lack the ...