vibetrack

by chroneus · MCP Server · ★ 29

About vibetrack

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.

deep-learningexperiment-trackingmachine-learningmcp-servermlflow-alternativemlopssummarywritertensorboard

Quick Facts

Stars29
Forks17
LanguagePython
CategoryMCP Server
Quality Score69.0733834327406/100
Last Updated2026-06-03
Created2026-04-02
Platformsmcp, python
Est. Tokens~300k

Compatible Skills

These tools work well together with vibetrack for enhanced workflows:

  • autoresearch-claude-code — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)
  • SkillZero — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (55%)

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Frequently Asked Questions

What is vibetrack?

vibetrack is Modern experiment tracking that follows you across servers, messengers, and LLMs.. It is categorized as a MCP Server with 29 GitHub stars.

What programming language is vibetrack written in?

vibetrack is primarily written in Python. It covers topics such as deep-learning, experiment-tracking, machine-learning.

How do I install or use vibetrack?

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.

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