Tensorus

Acerca de

This package offers a comprehensive Model Context Protocol (MCP) server and client, specifically designed to facilitate interactions with the Tensorus tensor database. It establishes a standardized interface, empowering AI agents and large language models (LLMs) to seamlessly perform a wide array of operations on tensor data. From managing datasets and ingesting new tensors to executing complex tensor computations and retrieving detailed information, Tensorus provides the foundational tools for integrating advanced tensor capabilities into AI-driven workflows.

Características Principales

• Demo mode with pre-configured mock data for testing and demonstration
• Comprehensive tensor manipulation tools via Model Context Protocol (MCP)
• Full dataset management capabilities, including creation, listing, and deletion
• MCP Server for tensor database operations with support for streamable HTTP
• Python client library for easy integration with MCP servers
• 0 GitHub stars

Casos de Uso

• Managing and performing operations on tensor datasets within an application
• Integrating AI agents and LLMs with Tensorus capabilities for data processing
• Developing custom applications that require standardized access to tensor database functionalities