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, ...

Even the best AI models are challenged to carry out tasks via MCP. New benchmarks show models struggle when tasks become more complex. More training of AI models is required that's specific to MCP use ...

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 ...

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, ...