Despite its benefits, MCP raises serious concerns about vendor lock-in. Humanity released it as an open source standard under the MIT license, but the reality is that MCP is the brainchild of humanity. It is not a neutral standard from international entities like the W3C or ISO. This means that humanity is the only custodian of its evolution and could shape its development in a way that favors its own AI model, like Claude, over its competitors.
MCP promises to resolve AI interoperability by streamlining access to external data, but if it defaults while under human control, the problem really doesn’t solve it. Simply shift control from a fragmented API to a single gatekeeper.
MCPs risk following the same path. If developers build integrations around Anthropic’s vision, they may later find themselves locked. There is no viable alternative depending on its updates, pricing, and policy.
Unlike browsers and mobile platforms, AI is not just a software category, it is the backbone of the industry of the future. Those who control how AI accesses and processes information form the entire market, from finance and healthcare to cybersecurity and education.
When MCPs have become the dominant standard, but under human control, it is:
The open source nature of MCP allows for contribution and fork, but the bigger problem is: Will the AI industry rally as a truly open standard behind it, or will it remain a human-dominated protocol that will ultimately resegregate AI interoperability under a single entity?
Why AI interoperability is not negotiable
A common language is essential for AI to scale responsibly. Without interoperability, AI development remains fragmented, leading to inefficiency, contradictions and limited innovation.
A unified future
Today, all major AI models require custom integrations to access external data. Developers need to manage a variety of APIs, formats, and permissions to create unnecessary complexity. This slows down AI adoption, increases costs, and leads to an inconsistent user experience. Universal standards like MCP can solve this, but only if they are really open and remain neutral.
Avoid walled gardens
High-tech companies have a long history of transforming open platforms into closed ecosystems. Apple’s iOS and Google’s Android started out as enablers, but evolved into a highly controlled environment that directs the terminology to developers. If MCPs are under human control, they run the risk of becoming similar systems. This is equally open, but ultimately designed to benefit one company’s ecosystem across a wider industry.
User’s perspective
End users (businesses, researchers, individuals) don’t need to worry about vendor lock-in when using AI tools. Interoperability benefits everyone by making AI systems run seamlessly across the platform, rather than trapping users within a single vendor ecosystem. When AI democratizes access to intelligence, it must be built on neutral and universally accepted protocols rather than on their own systems disguised as open standards.
Beyond MCP: For neutral governance
Neutral governance is essential for successful AI interoperability. When a company manages standards, it can determine access, influence competition, shape the future of AI in ways that serve its own profits rather than a wider industry.
Who owns the standard?
Currently, MCP is a human-led initiative, not an industry-wide standard supported by independent bodies like the IETF and ISO. This raises concerns about long-term neutrality. Without a move to a multi-stakeholder governance model, MCP could become an industry bottleneck rather than a true enabler of AI interoperability.
Community vs Control
Open source adoption does not automatically translate into shared governance. If MCPs acquire widespread use, important questions remain.
What happens if humanity decides to pivot that direction? Can competitors contribute meaningfully, or are they always at a disadvantage? How do independent organizations, governments, and businesses ensure that MCPs remain fair and impartial?
To be beyond the unique standards of MCP disguised, its roadmap must be shaped by an independent body representing the broader AI ecosystem. Otherwise, there is a risk that it will become another closure system that limits innovation and competition.
A call to action
There are two paths ahead.
The human hand that passes MCP governance to neutral AI standards organizations ensures that it remains open and fair protocols. The industry is creating independent alternatives and developing truly open AI interoperability standards that are not controlled by a single company.
Without any of these solutions, MCPs can simply shift AI interoperability issues from fragmented APIs to a single dominant gatekeeper.
AI leaders need to act now
The industry has the opportunity to prevent AI interoperability from becoming another unique battlefield. Instead of allowing a single company to decide the future of AI data exchange, key players must come together to establish a truly open standard.
To achieve this, AI leaders need to take immediate action, as follows:
Establish neutral governance institutions such as W3C, IEEE, or new AI-centric standard standards organizations to oversee AI interoperability. It encourages collaboration between major AI players such as Openai, Google, Microsoft, and Meta, preventing unique standards that compete with fragmentation. Driving discussions at major AI conferences such as Newlip, IEEE events, and Web Summits to gain industry-wide support and consensus.
The shared language of AI data exchange is important, but should not be determined by a single company. If the industry is waiting too long, MCPs or similar initiatives can solidify under corporate management, making it much more difficult to establish an independent, truly open alternative later. AI interoperability has time to act before it gets locked into a system that serves the profits of one company, rather than a broader ecosystem.
Stakes: The Unified Future of AI
The future of AI will depend on whether interoperability is built on open and comprehensive standards or controlled by a small group of companies.
Something at risk
When MCPs have become the dominant standard, but are under human control, the AI ecosystem can face serious challenges.
A fragmented AI landscape where systems are incompatible forces businesses to choose from a closed ecosystem. The AI market has dominated it. There, a small number of companies decide how AI evolves and limit access to small players. The future of AI shaped by the interests of the corporation rather than independent research, public opinion, or ethical considerations.
opportunity
If AI interoperability is handled correctly, it could level out the arenas for businesses, developers, and researchers. The truly open standards are:
It allows AI systems to communicate seamlessly, just as the Internet is working today. Developers will allow you to build without fear of vendor lock-in. Create a universal AI protocol that is as important and fundamental as the Internet TCP/IP.
Conclusion
MCP is a step in the right direction, but that’s not enough. AI interoperability must be governed by neutral, independent bodies to prevent vendor lock-in and ensure innovation remains open to everyone. Without industry-wide surveillance, AI could limit access, competition, progress and become another space dominated by several powerful players.
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