Large language models are ever more commonly handling sensitive data at scale. 📈
RAG Servers and MCP Servers serve completely different purposes. The security implications differ just as much, especially around database access. 🔒
Our latest blog delves into the differences so you can make an informed decision. Check it out 👉 https://www.pgedge.com/blog/rag-servers-vs-mcp-servers-choosing-the-right-approach-for-ai-powered-database-access
#programming #cybersecurity #compliance #pii #hipaa #ccpa #gdpr #privacy #dataprivacy #ai #llm #dataengineering #developers #mcp #rag #postgres
RAG Servers vs MCP Servers: Choosing the Right Approach for AI-Powered Database Access
As AI capabilities continue to evolve and integrate more deeply into our applications, we’re faced with interesting architectural decisions about how to expose our data to large language models (LLMs). Two approaches that have gained significant traction are Retrieval Augmented Generation (RAG) servers (such as pgEdge RAG Server) and Model Context Protocol (MCP) servers (such as pgEdge Natural Language Agent). Both have their place, but they serve quite different purposes and come with vastly different security implications – particularly when it comes to database access.





