Creating a custom Model Context Protocol (MCP) client using Gemini 2.5 Pro provides an opportunity to design a highly adaptable and efficient communication solution. By combining a robust backend, a ...

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; ...

Microsoft Corp. believes we’re headed toward a future where artificial intelligence-powered agents will become pervasive in enterprise computing environments, so today it’s making it easier for those ...

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 ...

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 ...

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 ...

Protect your AI agent workflows from quantum threats. Learn how to implement quantum-resistant cryptography for Model Context Protocol (MCP) deployments today.

As the development of AI tools accelerates, organizations are under increasing pressure to move models from prototype to production securely and with scalability. Behind the scenes, managing AI models ...

As part of the effort to push Large Language Model (LLM) ‘AI’ into more and more places, Anthropic’s Model Context Protocol (MCP) has been adopted as the standard to connect LLMs with various external ...

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 ...