Learn how this new standard connects AI to your data, enhances Web3 decision-making, and enables modular AI systems.

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 ...

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 ...

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 ...

Artificial intelligence startup Anthropic PBC today released a toolkit for connecting large language models to external systems. The Model Context Protocol, or MCP for short, is available under an ...

LLMs and AI tools have transformed nearly every industry, including marketing. We’ve become accustomed to AI’s ability to: But as these models evolve, their capabilities are entering a new phase with ...

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 ...

While working on a research paper, I decided to test one of the leading AI assistants and asked Anthropic’s Claude to analyze hundreds of emails and build a spreadsheet of recent Nobel Prize-winners.