Over a three-month period, clouddiver@gmail.com developed and enhanced the Model Context Protocol (MCP) server for the amzn/selling-partner-api-samples repository, enabling AI assistants to perform natural language queries on Amazon sales, traffic, economics, and inventory data. The work involved building a translation layer from natural language to GraphQL, supporting both seller and vendor analytics through separate, extensible packages. Using TypeScript, Node.js, and GraphQL, clouddiver implemented local storage for offline data access, introduced tools for file pagination, and standardized module imports. The engineering approach emphasized maintainability, clear documentation, and robust error handling, resulting in a reliable backend for data-driven decision making.
Monthly summary for 2025-07 focusing on key outcomes and business value for amzn/selling-partner-api-samples.
Monthly summary for 2025-07 focusing on key outcomes and business value for amzn/selling-partner-api-samples.
May 2025 monthly summary for amzn/selling-partner-api-samples: Delivered offline data capabilities and cleaned up legacy code paths to improve reliability and developer productivity. Implemented local storage for request results and offline document access in Amazon Data Kiosk, including directory creation fallbacks and a read-file tool for paginating locally stored content. Fixed key maintenance/consistency issues by removing the deprecated LLM context script (flatten-project.sh) and standardizing shared utilities import paths across server packages.
May 2025 monthly summary for amzn/selling-partner-api-samples: Delivered offline data capabilities and cleaned up legacy code paths to improve reliability and developer productivity. Implemented local storage for request results and offline document access in Amazon Data Kiosk, including directory creation fallbacks and a read-file tool for paginating locally stored content. Fixed key maintenance/consistency issues by removing the deprecated LLM context script (flatten-project.sh) and standardizing shared utilities import paths across server packages.
April 2025 Monthly Summary for amzn/selling-partner-api-samples: Delivered the MCP Server for Data Kiosk: Seller and Vendor Analytics, enabling natural-language querying of sales, traffic, economics, and inventory data by bridging the AI assistants with the Data Kiosk API. Implemented a Model Context Protocol (MCP) server that translates natural language requests into GraphQL queries, supporting separate seller and vendor analytics packages. This work lays the foundation for AI-assisted analytics and faster data-driven decision making across seller and vendor teams.
April 2025 Monthly Summary for amzn/selling-partner-api-samples: Delivered the MCP Server for Data Kiosk: Seller and Vendor Analytics, enabling natural-language querying of sales, traffic, economics, and inventory data by bridging the AI assistants with the Data Kiosk API. Implemented a Model Context Protocol (MCP) server that translates natural language requests into GraphQL queries, supporting separate seller and vendor analytics packages. This work lays the foundation for AI-assisted analytics and faster data-driven decision making across seller and vendor teams.
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