by chroneus · MCP Server · ★ 29
vibetrack Modern experiment tracking. Key features: Send experiment results elsewhere: Telegram, Slack, Jupyter, Gradio, and MCP. Run locally while receiving experiment data over the network via REST API. Use open formats: experiment data is stored in SQLite and local files. Compare image-to-image results. Use a rich UI to show, hide, delete, and customize runs. TensorBoard SummaryWriter compatible drop-in APIs. Query results through the MCP server. Fast scalar logging; see the benchmark report.
| Stars | 29 |
| Forks | 17 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 69.0733834327406/100 |
| Last Updated | 2026-06-03 |
| Created | 2026-04-02 |
| Platforms | mcp, python |
| Est. Tokens | ~300k |
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vibetrack is Modern experiment tracking that follows you across servers, messengers, and LLMs.. It is categorized as a MCP Server with 29 GitHub stars.
vibetrack is primarily written in Python. It covers topics such as deep-learning, experiment-tracking, machine-learning.
You can find installation instructions and usage details in the vibetrack GitHub repository at github.com/chroneus/vibetrack. The project has 29 stars and 17 forks, indicating an active community.