MCP server for TabICL — in-context tabular ML (classify, regress, explain, report) for LLM agents
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# TabICL MCP Server > **State-of-the-art tabular ML inside Claude or ChatGPT — share a CSV, ask a question, get predictions, explanations, and a report. Free and self-hostable.** [TabICL](https://github.com/soda-inria/tabicl) (Inria, ICML 2025/2026) is a tabular foundation model: it classifies and regresses on tabular data **without any hyperparameter tuning**, via in-context learning. This MCP server makes it usable from natural language in any MCP-compatible assistant or agent. ``` You: Here's my customer spreadsheet — who is likely to churn, and why? Claude: [load_data] → 2,340 rows, 12 columns, target "churned" looks binary [evaluate] → 89% accuracy, 0.93 ROC-AUC on held-out data [explain] → top drivers: contract_type, tenure, monthly_charges [create_report] → here's a shareable HTML report with the details… ``` ## Tools | Tool | What it does | |---|---| | `load_data` | Ingest a CSV — pasted text, a **URL** (Google Sheets share link, raw GitHub, any CSV URL), or a local file path. Returns a `dataset_id` so data is transferred once, not per call | | `evaluate` | "How well can you predict X?" from a single labeled CSV — honest held-out metrics (accuracy, balanced accuracy, F1, ROC-AUC, confusion matrix / R², RMSE, MAE) | | `predict` | Fit on labeled data, predict new rows — labels + per-row confidence (classification) or numbers (regression) | | `explain` | Which columns drive the predictions (permutation feature importance) | | `create_report` | Self-contained HTML report: metric cards in plain language, confusion matrix, feature importance chart, distributions. Served as a link (remote) or file (local) | | `export_predictions` | Page through large prediction results as CSV | **Data limits:** ~10k rows pasted inline, ~50k via URL or file. TabICLv2 handles 2–100 features natively. ## Try it in 60 seconds **Connect the public server to claude.ai** (Pro/Max/Team plans): 1. Go to **Settings → Connectors → Add custom connecto…
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