in-house AI context layer costs

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062026-11After MCP standardization: the infrastructure gap and the challenge of putting it into productionStack Overflow's blog argues that MCP has standardized AI tool interfaces, but the supporting infrastructure — context layers, hosting and governance — is still immature. Building an in-house AI context layer often costs companies more than they expect, and new products such as MCPCore and Orphex MCP on Product Hunt show the developer ecosystem shifting from protocol standards to competition over engineering services.Product Hunt、Stack Overflow Blog