Imagine a world where your AI tools don’t just work for you but work with each other—seamlessly, intelligently, and without the frustration of endless custom integrations. This isn’t a distant dream; ...

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 ...

An interface between an AI language model and external sources such as a database. The Model Context Protocol server (MCP server) determines what the model can access. The MCP client, typically an AI ...

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 ...

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 ...

What if the way AI agents interact with tools and resources could be as seamless as browsing the web? Imagine a world where developers no longer wrestle with custom-built adapters or fragmented ...

Claude’s Model Context Protocol promises a new way to handle context across tools and systems. The goal is to improve how ...

The Model Context Protocol (MCP)—a rising open standard designed to help AI agents interact seamlessly with tools, data and interfaces—just hit a significant milestone. Today, developers behind the ...

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 ...

Struggling with MCP authentication? The November 2025 spec just changed everything. CIMD replaces DCR's complexity with a ...