MCP server for building reproducible, interoperable scientific workflows on stamped data (time, depth, frequency, ...).
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# sciflow-mcp An MCP server that lets scientists and their agents build **reproducible, interoperable analysis workflows** over stamped data: data positioned along time, cortical depth, frequency, or any other parametric axis. It builds on three earlier pieces of work: - **[Collate](https://github.com/cardin-higley-lab/Collate)**: every array is paired with a stamp per sample, and multiple acquisition systems are aligned to one clock. Its `GeneralizedData` successor generalizes time to any parametric axis. - **[EventLogic](https://github.com/Claybarn/EventLogic)**: logical operations (AND, OR, NOT, merge, containment) on `[on, off]` intervals. - **The generalized analysis functions** from [Barnes et al. 2026](https://github.com/cardin-higley-lab/Barnes_et_al_2026): peri-event collation, normalization and correlation that work whatever the data's dimensionality. ## Install ```bash git clone https://github.com/Claybarn/sciflow-mcp && cd sciflow-mcp && uv sync ``` Opening the repo in Claude Code picks up the server from [.mcp.json](.mcp.json). For other MCP clients, see [MCP tools](#mcp-tools). ## Why it interoperates There are exactly two artifact kinds. Both lie on a named **parametric axis** with a unit (`time` in `s` by default): | kind | contents | invariant | |---|---|---| | `series` | N-D `data`, 1-D `stamps`, axis labels, coordinates, `stamp_unit` | `len(stamps) == data.shape[0]`, stamps finite and non-decreasing, **the parametric axis is always axis 0** | | `intervals` | sorted `ons`, `offs`, `axis`, `unit` | `on <= off`; point events have `on == off` | - **Workflows are type-checked before they run.** Every operation declares which kinds it takes and which it returns. - **No `parametricAxis` argument.** The parametric axis is always axis 0, so `peri_event` works the same on a 1-D wheel trace, a channels × time LFP and a 32 × 32 × time imaging stack. - **Axes can't be mixed silently.** Operations that combine artifacts require the same parametric ax…
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