An MCP server that maps your ML / GNN workflow as a node graph and records every experiment as a branching tree, while Codex or Claude Code works.
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# mltree-mcp [](https://github.com/yboulaamane/mltree-mcp/actions/workflows/test.yml) [](https://pypi.org/project/mltree-mcp/) [](https://pypi.org/project/mltree-mcp/) [](https://github.com/yboulaamane/mltree-mcp/blob/main/LICENSE) **Your ML workflow as a node map, your experiments as a tree — filled in by your coding assistant as it works.** `mltree-mcp` is an [MCP](https://modelcontextprotocol.io) server for Codex, Claude Code and any other MCP client. While the assistant writes and runs your ML / QSAR / GNN code, it calls `mltree` tools to: - register each pipeline step (load → clean → featurize / graph-build → split → HPO → train → evaluate) as a **node**, with its own `.py` script, inputs, outputs and default params; - wire the steps into a **DAG**; - log every execution as a **run** with params, metrics and artifacts, branching from a parent run (HPO trials, GNN variants…), so experiments form a **mind-map tree** instead of being scattered down a notebook. Everything lives as plain files in your repo under `.mltree/`, and `mltree-mcp view` opens a KNIME-style map of it in your browser.    > Status: **0.8.0**. MCP core, map viewer, `scan_project` for existing projects, shareable HTML export, running steps > and grid sweeps from the map (opt-in), data versions, compare with param changes / curves / code diffs, notes and > tags, GNN views, and now **PyPI p…
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