Instead of each AI integration being custom-coded for every app, MCP provides a shared standard, so MCP-compliant systems can ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

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 past ten years have seen incredible advancements in the realm of Artificial Intelligence, but paradoxically, some of the most overt shortcomings of AI are still based not on intelligence but on ...

As AI becomes central to GTM strategy, the challenge is no longer adoption but integration. Data remains locked inside walled ...

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 ...

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 ...

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 ...

People.ai's SalesAI Platform now brings in structured and unstructured interaction data through MCP integration.

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 ...