Model Context Protocol
How MCP became enterprise infrastructure, how to build governed MCP servers, and why standardizing on the protocol still needs a semantic layer behind it.
The Model Context Protocol (MCP) is the open standard, introduced by Anthropic in November 2024 and now governed by the Linux Foundation's Agentic AI Foundation, for connecting AI applications to tools, data, and systems. It collapses the M-by-N integration problem into M-plus-N: write your system as one MCP server, and any MCP client can reach it.
This collection covers MCP from the enterprise architect's point of view. Posts here examine the adoption evidence and governance model that make MCP a real infrastructure decision, the exact wire shapes and code for building a governed MCP semantic layer server, and the semantic gap the protocol leaves open. MCP standardizes access. It does not standardize meaning. These pieces argue that the winning enterprise pattern pairs MCP as the transport with a governed semantic execution layer as the logic.
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Enterprise MCP Adoption: Why the Model Context Protocol Became Infrastructure
The Linux Foundation donation, the version timeline, cross-vendor support, and why standardizing on MCP still needs a governed semantic layer.
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APIs vs MCP vs A2A: What Enterprise AI Teams Need to Know
A cited comparison of APIs, MCP, and A2A, a three-question decision framework, and why none of them solve the meaning problem.
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How to Build an MCP Semantic Layer Server (Architecture, Code, and the No-Rip-and-Replace Case)
The protocol in two minutes, the exact message shapes a semantic-layer server speaks, a buildable FastMCP scaffold, and the cost argument for MCP over a custom API.
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