AI vendors agree on almost nothing publicly — not pricing, not benchmarks, not which model is "best." Which is why it's worth paying attention when Anthropic, OpenAI, Google, Microsoft, Salesforce, AWS, and Cloudflare all end up backing the same piece of infrastructure. That's what happened with the Model Context Protocol (MCP), and it changes a real, practical decision for anyone building or buying AI right now: what you build your integrations on.
What MCP Actually Is
MCP is an open standard, originally built by Anthropic, for connecting an AI model to the systems where your actual data lives — your CRM, your internal knowledge base, your codebase, your ticketing system. Before MCP, connecting an AI assistant to five different business tools meant building five different custom integrations, each with its own quirks, and rebuilding them again if you switched AI providers. MCP replaces that with one protocol: build an "MCP server" for your data source once, and any MCP-compatible AI client can connect to it — Claude, ChatGPT, Gemini, GitHub Copilot, Cursor, VS Code, and a growing list of others.
Why the Governance Change Is the Actual News
MCP launched in November 2024 as an Anthropic project. The more significant development came in December 2025, when Anthropic donated MCP to the newly formed Agentic AI Foundation, a directed fund under the Linux Foundation, co-founded by Anthropic, Block, and OpenAI — with AWS, Google, Microsoft, Cloudflare, and Bloomberg joining as platinum members. That matters practically, not just symbolically: a protocol controlled by one AI vendor is a lock-in risk. A protocol governed by a neutral foundation with your other vendors already at the table is closer to a genuinely safe long-term bet, the same way businesses trust HTTP or SQL precisely because no single company can unilaterally change the rules.
The Adoption Numbers Back Up the Consensus
This isn't a standard adopted on paper and ignored in practice. MCP crossed 97 million monthly SDK downloads by March 2026, up from roughly 100,000 at launch, with over 10,000 active MCP servers in production use. Salesforce made Hosted MCP Servers generally available for every Enterprise Edition org in April 2026. When a protocol goes from zero to this level of production usage inside about eighteen months, across competing vendors who have every incentive to build competing standards instead, that's a signal worth acting on.
What This Actually Means If You're Building or Buying AI Right Now
If you're building custom AI features, architecting your integrations as MCP servers from the start — rather than one-off API connections tied to a specific model provider — means you're not locked into a single AI vendor's roadmap. Swapping the underlying model later becomes a configuration change instead of a rebuild. We cover the broader architecture this fits into in our LLM application development guide.
If you're evaluating an AI vendor or SaaS tool, ask directly whether their AI integrations are MCP-based or proprietary. A proprietary integration isn't automatically wrong, but it's worth knowing you're accepting that lock-in deliberately rather than by default — this is exactly the kind of question we recommend asking in our enterprise AI vendor evaluation checklist.
If you're already running AI agents or RAG pipelines in production, this doesn't require an urgent rebuild — but it's worth reviewing whether your next integration project defaults to MCP or to another one-off connector, since that decision compounds over every future integration you add.
Where This Fits Into the Bigger Picture
MCP solves the "how does the model talk to my systems" problem, not the "is the AI actually grounded in my data correctly" problem — that's still an architecture decision that depends on retrieval quality, guardrails, and evaluation, which we cover in our guide to building production-grade RAG pipelines. A standard integration protocol makes AI projects faster and less locked-in to build; it doesn't replace doing the grounding and evaluation work properly.
If you're scoping an AI integration project and want it built on infrastructure that won't lock you into one vendor's roadmap, reach out at info@digit.com.pk — we build against MCP by default now, precisely because betting on a proprietary integration layer is a bet we'd rather not make on your behalf.