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datarust workspace

This repository is a Cargo workspace hosting the datarust ecosystem: a collection of independent, separately-versioned crates for classical data-science and machine-learning workloads in Rust.

Crates

Crate

Path

Description

[datarust]

crates/datarust/

Scikit-learn-style preprocessing and classical ML in Rust. Standard/minmax/robust scalers, encoders, imputers, PCA, linear models, decision trees & random forests (bit-exact sklearn parity), clustering, pipelines — zero external dependencies by default.

[datarust-profile]

crates/datarust-profile/

One-call data profiling and data-quality reports. Column statistics, distribution shape, pairwise relationships (Pearson, Cramér's V, point-biserial), target-leakage hints, quality findings, CSV ingestion, single-pass streaming, a CLI — HTML/JSON/terminal output.

[datarust-mcp]

crates/datarust-mcp/

Model Context Protocol (MCP) server implementation for Claude Desktop, Cursor, and AI agents. Exposes data profiling, training, and preprocessing over stdio JSON-RPC.

Each crate has its own README.md, CHANGELOG.md, version, and release track, and is published independently to crates.io.

Related MCP server: Kaggle Dataset Analyst

Model Context Protocol (MCP) Server

This repository contains the official MCP server implementation in crates/datarust-mcp.

Running Locally (Stdio)

cargo run --release -p datarust-mcp

Claude Desktop / Cursor Setup

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "datarust": {
      "command": "cargo",
      "args": ["run", "--release", "--manifest-path", "/path/to/datarust/Cargo.toml", "-p", "datarust-mcp"]
    }
  }
}

Available Tools

  • profile_dataset: Profiles CSV data, computing descriptive stats, distribution shapes, and quality checks.

  • train_linear_regression: Fits OLS linear regression with exact scikit-learn parity.

  • scale_features: Feature scaling via StandardScaler, MinMaxScaler, or RobustScaler.

  • evaluate_metrics: Computes R², MSE, RMSE, MAE, and accuracy metrics.

Agent Platform Configs & Official Skills

This repository provides pre-configured agent instructions and official Agent Skills for autonomous coding agents:

Documentation

Working in this workspace

# Build / test every crate
cargo build --workspace
cargo test  --workspace

# Work on a single crate
cargo test -p datarust --all-features
cargo test -p datarust-profile --features serde

# Build the static docs/blog site (Node 22+)
npm install
npm run build && npm run check

The workspace root Cargo.toml carries a [patch.crates-io] entry that points datarust-profile at the local source tree of datarust during development. This patch is ignored by cargo publish, so published crates depend on the crates.io release as normal.

License

MIT — see each crate's LICENSE.

Related MCP Connectors

Related MCP Servers

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