Crosstabs Mcp
Same crosstab statistics as the sibling `crosstabs` package, registered under the PyPI name crosstabs-mcp for MCP clients that expect that identifier.
Overview
io.github.barangaroo/crosstabs-mcp is a Grow-phase MCP server (PyPI name crosstabs-mcp) that exposes contingency-table statistics including chi-square and Fisher’s exact tests to your coding agent.
What is this MCP server?
- Identical statistical scope: chi-square, Fisher’s exact, odds ratio, effect sizes
- PyPI identifier crosstabs-mcp v1.0.0 with stdio MCP
- Same crosstabs-lite repo (mcp-server-python subfolder) as barangaroo/crosstabs
- Pick this listing when your install docs or lockfile already reference crosstabs-mcp
- stdio-only; no bundled remote HTTP endpoint in registry metadata
- Server version 1.0.0
- PyPI identifier crosstabs-mcp, stdio transport
- Shared GitHub repo barangaroo/crosstabs-lite, mcp-server-python subfolder
What problem does it solve?
Your project already depends on the crosstabs-mcp PyPI name but you still need agent-driven significance tests on category tables without manual stats software.
Who is it for?
Builders whose MCP or Python setup already references crosstabs-mcp and who need categorical significance testing in-agent.
Skip if: Anyone who can install the newer crosstabs 1.0.2 package instead and wants the latest registry version—unless you are locked to this package name.
What do I get? / Deliverables
You keep a stable package identifier while your agent outputs the same crosstab inferential statistics for decisions in analytics reviews.
- Inferential tests and effect measures for your crosstab
- Consistent stats output under the crosstabs-mcp package name
- Documentation-ready significance summaries from the agent
Recommended MCP Servers
Journey fit
Growth-phase analytics is where categorical experiment and survey tables get interpreted; this duplicate package name serves the same statistical workflow on the canonical Grow shelf. Formal tests on cross-tabs support analytics subphase decisions—whether a channel, persona, or feature flag split behaves differently in the data.
How it compares
Duplicate PyPI entry for the same crosstabs-lite MCP server—not a different statistical engine or marketplace skill.
Common Questions / FAQ
Who is io.github.barangaroo/crosstabs-mcp for?
Solo developers using MCP who install via the crosstabs-mcp PyPI package and want contingency-table stats inside Claude Code or Cursor.
When should I use io.github.barangaroo/crosstabs-mcp?
When your environment specifies crosstabs-mcp, or you are following docs that register this exact server name rather than crosstabs.
How do I add io.github.barangaroo/crosstabs-mcp to my agent?
pip install crosstabs-mcp (1.0.0), add an stdio MCP server block with that package’s launch command, and reload your agent’s MCP configuration.