Why MCP became the standard for AI tools
In roughly a year, the Model Context Protocol went from a quiet Anthropic release to the default way AI applications connect to outside tools. AECdesign.ai is built on it — so it's worth understanding why it won. (New to the term? The FAQ covers the basics; this goes a level deeper.)
The short history
Anthropic published MCP as an open standard in late November 2024. It was well received but quiet at first. Adoption broke open in 2025: OpenAI added MCP support across its Agents SDK and products in March 2025, and Google confirmed support for its Gemini models in April 2025 — at which point Google DeepMind's Demis Hassabis described it as "rapidly becoming an open standard for the AI agentic era." By late 2025 there were thousands of MCP servers in the wild.
Why a shared protocol wins
Before a standard, every AI-tool integration was bespoke: connecting M AI apps to N tools meant building and maintaining roughly M×N custom integrations. A shared protocol collapses that to M+N — each app and each tool implements MCP once. The decisive feature of any protocol is who already speaks it, and once the largest model providers committed, the network effect did the rest.
What this means for an AEC firm
It means an AEC review tool can ride shared infrastructure instead of a one-off, proprietary vendor integration that may not outlive the vendor. AECdesign.ai exposes its review tools as MCP tools inside Claude Desktop — the same client your team uses for everything else — rather than asking you to adopt yet another standalone platform. Building on the standard is a bet that the connection layer will still be here in five years.
Sources
- Model Context Protocol — Wikipedia (launch Nov 2024; OpenAI Mar 2025; Google Apr 2025).
- Why MCP Won — Latent.Space (Mar 10, 2025).
- The Model Context Protocol's impact on 2025 — Thoughtworks.
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