Azure Table Storage

This Azure Table Storage MCP server, developed by Christia Pedersen, provides AI assistants with a standardized interface to interact with Azure Table Storage. Built using TypeScript and leveraging the @azure/data-tables library, it offers capabilities for storing, retrieving, and querying structured data in the cloud. The server abstracts the complexities of Azure Table Storage operations, handling authentication, data serialization, and query optimization. It's particularly valuable for developers and AI systems working with large-scale, semi-structured data, enabling use cases such as log data storage, user profile management, and IoT telemetry processing within the Azure ecosystem.