leaderboard_get_pareto_frontier – 1 MCP server offers this tool
What it usually takes
benchmark– in 1 of 1beyond_features– in 1 of 1beyond_size– in 1 of 1beyond_split– in 1 of 1cost– in 1 of 1datasets– in 1 of 1entrants– in 1 of 1imputation– in 1 of 1kind– in 1 of 1max_predict_time_s_per_1k– in 1 of 1max_train_time_s_per_1k– in 1 of 1quality– in 1 of 1
No server marks it as only reading: treat it as able to change data.
From each publisher's own tool list. We never call a tool.
Servers
| Server | Inputs | Read-only? |
|---|---|---|
TabArena co.huggingface.tabarena/leaderboard The accuracy-versus-time trade-off among tabular models (TabPFN, TabICL, LightGBM, XGBoost, CatBoost, RealMLP, AutoGluon and the rest), measured on TabArena or BeyondArena. Returns the outright best model, the models nothing beats on both accuracy and speed at once (each with its speedup and accuracy gap versus the leader), and the best model that fits a train- or predict-time budget. Prefer it over the leaderboard endpoints for 'which model should I use on my tabular data', 'what is the best tabular model', 'what is a faster alternative to TabPFN', or anything about cost of training or serving: the top of the leaderboard is often orders of magnitude slower than a model just behind it. Returns a summary sentence you can relay. | benchmark,beyond_features,beyond_size,beyond_split,cost,datasets,entrants,imputation,kind,max_predict_time_s_per_1k,max_train_time_s_per_1k,quality,splits,tasks | Not stated |