Summary
Optimisation you can interrogate while it runs.
Optuna is usually driven from a script and read from a dashboard. Here the study is created, sampled and inspected in the same conversation, so why it settled where it did is answered by pulling the trials rather than by re-running anything.
What it is
An interface to Optuna, the hyperparameter optimisation framework. A study is created and configured through tool calls and its trials are read the same way, so running the optimisation and analysing it happen in one place.
What you get
- Studies created, and every study name on the storage listed
- A study's optimisation directions, and its metric names read or set
- The trials of a study, returned for analysis
- The sampler chosen for a study
- Results persisted when you point the study at a storage backend — a local SQLite file keeps them across sessions
Requirements
A recent Python, installed with uv or run from Docker. Without a storage backend the study lives only for the session; point it at one and it is kept.
Setup effort
One command — uvx optuna-mcp