Local AI training platform with sports sync

Open-source local platform for AI training, syncing sports data (Garmin, WHOOP) with a TypeScript SDK and MCP server.

Local AI Training Platform with Sports Sync

This open-source platform provides a robust local environment for AI model training, specifically designed to integrate and synchronize personal sports data. Leveraging a TypeScript SDK and an MCP server, it offers developers a direct pathway to build and deploy AI applications that can utilize real-world physiological and performance metrics. The focus is on providing a self-contained, controllable training pipeline for AI builders who require data privacy and customizability.

What it Does

The platform facilitates the local training of AI models by providing the necessary infrastructure and tools. A core function is its ability to synchronize data from popular sports tracking devices and services, such as Garmin and WHOOP. This synchronized data is then made available through a TypeScript SDK, allowing developers to access and process it within their AI training workflows. The integrated MCP server acts as a backend for managing these data streams and model interactions.

Key Features

Open-Source: Full access to source code for customization and transparency.
Local Training: Enables AI model training entirely on your own infrastructure, ensuring data privacy.
Sports Data Sync: Integrates with Garmin and WHOOP devices for seamless data import.
TypeScript SDK: Provides a modern, type-safe interface for data access and manipulation.
MCP Server: Facilitates backend operations and communication for AI applications.

Who it's For

This tool is ideal for AI developers, data scientists, and researchers who are building AI applications that require personalized or performance-based data. It's particularly suited for those working on projects related to fitness, health, athletic performance analysis, or any domain where real-time physiological data can enhance AI model accuracy and utility. Developers prioritizing data sovereignty and seeking a flexible, local training environment will find this platform highly beneficial.