DataHawk MCP lets any AI assistant — Claude, ChatGPT, Cursor, n8n, Make, Lovable, Replit, or your own agent — talk directly to your Amazon data. Ask a question in plain English, get a grounded answer from your actual DataHawk workspace. No SQL, no waiting.
MCP stands for Model Context Protocol — an open standard for connecting AI assistants to external data sources and tools. Think of it as USB-C for AI: one server, every AI client.
For a deeper primer, see Anthropic's MCP introduction.
DataHawk runs an MCP server that exposes your Amazon data to any MCP-compatible AI. The AI discovers what's available automatically, picks the right tool for the question, and returns a real answer grounded in your workspace.
Amazon data lives across SP-API, the Ads API, vendor reports, brand analytics, DSP exports, and a dozen other surfaces. Getting a clean answer to a simple question — which products drove growth last month? — normally means stitching reports together, reconciling currencies, and chasing marketplace-specific quirks.
DataHawk already does that stitching. MCP lets you talk to the result in natural language, from whatever AI tool you already use.
Instead of spending weeks building SP-API and Ads API integrations yourself, you plug into DataHawk and get everything — sales, ads, inventory, catalog, SEO, traffic, DSP, finance, vendor — ready to query.
No more writing queries or navigating dashboards. Just ask:
Your AI assistant routes the question, picks the right data views, validates the query, and returns the answer — with numbers grounded in your actual DataHawk account.
DataHawk MCP includes a dedicated investigation flow for diagnostic questions like why did revenue drop last week? or what's driving the ACOS spike on Brand X?