Most people think the biggest factor in AI performance is the model.
But often in enterprise settings, the architecture behind how internal data is connected matters even more.
A new benchmark from CData found a ~25% accuracy gap between different MCP server approaches.
Basically, two AI systems using the same model could return very different answers depending on how they access your data and what approach to MCP they use.
If you’re building AI agents, copilots, or internal tools that connect to CRM or project management systems… this is worth understanding.
You can check out the full benchmark, methodology & results from CData here:
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