SciTeX – Modular Python Toolkit for Researchers and AI Agents

A Python framework for reproducible scientific research.

Role in SciTeX Ecosystem

scitex is the unified orchestrator package. It re-exports from sub-packages so users have a single import (import scitex). It does not contain runtime logic itself – it delegates to sub-packages.

scitex (this package) -- orchestrator, templates, CLI, MCP server
  |-- scitex.app  <-  scitex-app   (runtime SDK: file I/O, config, validation)
  |-- scitex.ui   <-  scitex-ui    (React/TS components: workspace, data-table)
  +-- scitex.plt  <-  figrecipe    (figures: plotting, diagrams, recipes)

scitex-app (docs): Runtime SDK that apps import at execution time
scitex-ui (docs): Shared React/TypeScript component library
figrecipe (docs): Reference app – figures, diagrams, recipes

Four Freedoms for Research

The freedom to run your research anywhere – your machine, your terms.
The freedom to study how every step works – from raw data to final manuscript.
The freedom to redistribute your workflows, not just your papers.
The freedom to modify any module and share improvements with the community.

AGPL-3.0 – because research infrastructure deserves the same freedoms as the software it runs on.

import scitex as stx

@stx.session
def main(n_samples=100, plt=stx.INJECTED):
    import numpy as np
    x = np.linspace(0, 2 * np.pi, n_samples)
    y = np.sin(x) + np.random.normal(0, 0.1, n_samples)

    fig, ax = plt.subplots()
    ax.plot_line(x, y)
    stx.io.save(fig, "sine.png")       # PNG + CSV + YAML recipe
    return 0

@stx.session – Reproducible runs with CLI, config, and provenance tracking
stx.io – Save/load 30+ formats through a single interface
stx.plt – Publication figures with auto CSV data export
stx.stats – 23 statistical tests with effect sizes and CI
stx.scholar – Search, download, and enrich papers
120+ MCP tools for AI-assisted research workflows

Getting Started