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 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 (MCP) is an open standard that enables developers to build secure, two-way connections between their data sources and AI-powered tools. The architecture is straightforward: ...

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 ...

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) for agentic AI has gained much traction since being introduced by Anthropic last November, and now it has a C# SDK. The MCP is a standard for integrating large ...

Anthropic recently released their Model Context Protocol (MCP), an open standard describing a protocol for integrating external resources and tools with LLM apps. The release includes SDKs ...

Artificial intelligence is progressing rapidly, but there is one issue that many people do not discuss enough: context. Even the most intelligent systems are not very effective when they lack a clear ...

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 ...

Anthropic today released a new open source protocol to let all AI systems, not just its own, connect with data sources via a standard interface. Model Context Protocol (MCP), the company said in its ...