Datadoe Launches Amazon Data MCP For Claude, Chatgpt And Cursor

(MENAFN- EIN Presswire) EINPresswire/ -- DataDoe, Inc. has launched Amazon Data MCP, a Model Context Protocol server and data layer that gives Amazon sellers, vendors, agencies and developers a cleaner way to bring live business data into AI tools such as Claude, ChatGPT, Cursor, Claude Code and other MCP-compatible environments.

Most ecommerce teams are not short on AI tools anymore. They are short on systems those tools can actually use. For Amazon operators, the data needed for real decisions is spread across Seller Central, Vendor Central, Amazon Ads, FBA inventory, settlement reports, refunds, returns, fees and internal cost data. That fragmentation makes AI workflows slower than they should be.

In practice, teams still export CSV files, copy numbers between reports, upload spreadsheets and explain each metric before an AI assistant can answer a basic business question. DataDoe is built to remove that manual layer.

The platform organizes Amazon data into a consistent, AI-ready Amazon data layer that can be used for analytics, API access, BigQuery workflows, exports and AI applications. With Amazon Data MCP, teams can give AI assistants permissioned access to structured Amazon data instead of relying on screenshots, stale spreadsheets or one-off report downloads.

For sellers and operators, this makes AI more practical in day-to-day work. Teams can ask which SKUs lost margin after advertising spend and FBA fees, which campaigns created profitable growth, where inventory risk is building, or how a marketplace performed after refunds, returns and currency effects. Agencies can create account summaries and client reports from live data. Developers can build dashboards, alerts, internal tools and AI agents without maintaining their own Amazon SP-API infrastructure.

The launch reflects a message DataDoe shared at an ecommerce conference in Las Vegas earlier this year:“AI agents won't scale your business. Systems will.”

“You can't just add another AI tool and expect it to transform the organization,” said Kris Krokos, Co-Founder of DataDoe.“The companies that win will build structured AI systems with clean access to real operational data. AI cannot sit in a silo. Its value comes from understanding the context of the business.”

DataDoe is starting with Amazon because it is one of the clearest examples of fragmented ecommerce data. Sellers and vendors work across orders, ads, inventory, fees, settlements, returns and marketplace-level reporting, but that data often sits in disconnected systems. The company is already testing additional marketplaces with the goal of becoming a reliable data layer for AI implementation across ecommerce businesses.

DataDoe is not trying to become another AI interface. The company is focused on the operational layer underneath it: the clean, structured business data that AI systems need in order to be useful. As AI tools become more capable, ecommerce teams will need a foundation that lets those tools understand the actual state of the business across marketplaces, channels and internal systems.

DataDoe's MCP layer keeps the Amazon data foundation separate from the AI interface. Teams can use Claude for analysis, ChatGPT for internal workflows, Cursor for development, or API and warehouse access for reporting without rebuilding the underlying Amazon connection every time.

Teams that want to connect Amazon data to Claude can use DataDoe's Claude integration page to see how MCP connects Amazon context with AI assistants. The broader platform also supports Amazon data access for analytics teams, developers, agencies and AI builders working across reporting, automation and operational decision-making.

DataDoe is available at DataDoe for Amazon sellers, vendors, agencies and software teams that need a cleaner foundation for Amazon analytics, reporting and AI-native commerce operations.

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