# ml-party

**An agent-native platform for ML experiment tracking and lineage/knowledge.**

A durable, agent-legible knowledge substrate for ML work — a lab notebook
that agents write (over MCP) and query, and that humans read live (CLI +
web UI) — that also happens to be a full local tracker: metrics, artifacts,
checkpoints, reproducibility, all stored locally.

Linux/macOS (Windows via WSL), Python ≥ 3.11. The web UI ships prebuilt in
the wheel:

```bash
pip install mlparty

mlp init --root .mlparty                    # create a store (+ MCP registration)
python -m mlparty.demo &                    # a real run: contract + live metrics
mlp ui                                      # → http://127.0.0.1:7327
```

To develop against a checkout instead, see
[From source](https://github.com/paul-krug/ml-party#from-source) (adds Node
≥ 20 for the UI build).

From there: agents pick up the MCP server automatically and it teaches them
the workflow ({doc}`mcp`); training scripts attach as the second writer
({doc}`tracking`); humans watch live in the web UI ({doc}`ui`); registered
actions let agents drive jobs, audited ({doc}`actions`).

```{toctree}
:maxdepth: 2
:caption: User guide

tracking
ui
boards
actions
mcp
remote
deploy
```

```{toctree}
:maxdepth: 1
:caption: Reference

api
design
changelog
```