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Many great points. I think we are thinking about MCP the wrong way.

The greater problem is industry misunderstanding and misalignment with what agents are and where they are headed.

Web platforms of the world believe agents will be embedded in networked distributed infrastructure. So we should ship an MCP platform in our service mesh for all of the agents running in containers to connect to.

I think this is wrong, and continues to be butchered as the web pushes a hard narrative that we need to enable web-native agents & their sdks/frameworks that deploy agents as conventional server applications. These are not agents nor the early evolutionary form of them.

Frontier labs will be the only providers of the actual agentic harnesses. And we are rapidly moving to computer use agents - MCP servers were intended to serve as single instance deployments for single harnesses. ie. a single mcp server on my desktop for my Claude Desktop.



Exactly. The problem isn't that MCP is poorly designed for enterprise uses, it is that LLMs are being used for things where they are not appropriate.

> In financial services, this means a trading AI could misinterpret numerical types and execute trades with the wrong decimal precision.

If you are letting an LLM execute trades with no guardrails then it is a ticking time bomb no matter what protocol you use for the tool calls.

> When an AI tool expects an ISO-8601 timestamp but receives a Unix epoch, the model might hallucinate dates rather than failing cleanly.

If your process breaks because of a hallucinated date -- don't use an LLM for it.




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