"Large language models (LLMs) are much the same. They carry vast general knowledge yet lack the specific context that makes them immediately valuable to your organization. Just like new hires go through the onboarding ropes, LLMs need structured access to your business's data, tools, and workflows to become truly useful. That's where Model Context Protocol (MCP) comes in. MCP enables communication between AI applications, AI agents, applications and data sources."
"MCP is not just another integration layer. It's a way to unlock latent value across your organization by connecting AI agents with the systems, data, and workflows that drive outcomes. The real opportunity lies in how you apply MCP. Start with what and why Let's be honest, there's no shortage of MCP primers out there. Most of them walk you through the architecture: hosts, clients, servers. That's fine, but it's not where the real value is."
New college graduates and LLMs both possess broad capabilities but lack organization-specific context needed for immediate impact. Model Context Protocol (MCP) provides structured, secure connections between AI agents, applications, and enterprise data sources to give LLMs the contextual access required to drive outcomes. MCP has evolved from an emerging standard into a strategic enabler, shifting focus from architecture to practical application. Organizations should prioritize the problems to solve and desired outcomes before designing MCP integrations. Secure, scalable, and compliant access to sensitive data, such as EHRs for personalized treatments, is a primary strategic hurdle MCP addresses.
Read at Fast Company
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