One of the biggest issues with large language models (LLMs) is working with your own data. They may have been trained on terabytes of text from across the internet, but that only provides them with a ...

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: ...

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 ...

Palo Alto bought Portkey, Solo.io gave agentgateway to the Linux Foundation. Agent gateways are consolidating into a category ...

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, ...

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 ...

Reuters today announced the launch of its Model Context Protocol (MCP) server, a new AI-native integration designed to power ...

As artificial intelligence applications proliferate across healthcare, the model context protocol is an emerging industry standard that defines how AI systems, large language models and agent-based ...

Spring AI 2.0 advances the Java framework for generative AI apps with a Spring Boot 4 baseline, cleaner agentic tooling, Model Context Protocol support and vendor-backed integrations including Azure ...