LinkedIn·Tuesday, 18 August 2026·8d ago
"Build an overview dashboard with my Shopify, HubSpot and Stripe data." That prompt fails when the AI client is wired to APIs. Not because…
Peliqan
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"Build an overview dashboard with my Shopify, HubSpot and Stripe data."
That prompt fails when the AI client is wired to APIs. Not because the model is weak. Because the question spans three systems that share no common definitions, and the agent gets raw objects from each with no way to reconcile them.
Which leaves two workarounds, both bad.
→ Connect the agent directly to production. Few IT teams will approve that for an ERP or a CRM.
→ Or export everything and join it by hand in a spreadsheet. Which is exactly where you started.
Give the agent a data warehouse instead of APIs.
→ All your systems land in one place, 300+ connectors
→ Definitions get modelled once in SQL or low-code Python, so revenue means the same thing in every answer
→ One MCP endpoint sits on top
Claude, ChatGPT, Copilot, any MCP client. Same governed data underneath, so two people asking the same question get the same number.
The result is the part that matters. Your finance lead asks in their own words and gets the answer your analyst would have given them next week.
Peliqan. The trust layer for AI.
#MCP #AIagents #DataStack
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