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, ...

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

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

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 ...

Is the Model Context Protocol the missing link in AI? Discover how MCP standardizes AI-tool communication, introduced by Anthropic to shape the future of AI integration.

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 ...

Tools, agents, UI, and e-commerce - of course each one needs its own set of competing protocols MCP, A2A, ACP, or UTCP? It ...

Anthropic’s model context protocol (MCP), the ‘plug-and-play bridge for LLMs and AI agents’ to connect with external tools, has received a major update one year after its launch. The developer of ...