MCP Server

SciTeX Stats provides a Model Context Protocol (MCP) server, enabling AI agents to run statistical tests and format publication-ready results autonomously.

Installation

pip install scitex-stats[mcp]

Starting the Server

scitex-stats mcp start

MCP Client Configuration

Add to your MCP client configuration (e.g., Claude Desktop, Cursor):

{
  "mcpServers": {
    "scitex-stats": {
      "command": "scitex-stats",
      "args": ["mcp", "start"]
    }
  }
}

Available Tools

**Table 1.** Ten MCP tools for AI-assisted statistical analysis. All tools accept JSON parameters and return JSON results.
Tool	Description
`recommend_tests`	Recommend appropriate tests based on data characteristics
`run_test`	Execute a statistical test on provided data
`format_results`	Format results in journal style (APA, Nature, etc.)
`power_analysis`	Calculate statistical power or required sample size
`correct_pvalues`	Apply multiple comparison correction (FDR, Bonferroni, etc.)
`describe`	Calculate descriptive statistics
`effect_size`	Calculate effect size between groups
`normality_test`	Test whether data follows normal distribution
`posthoc_test`	Run post-hoc pairwise comparisons
`p_to_stars`	Convert p-value to significance stars

Diagnostics

scitex-stats mcp doctor          # Check dependencies and server health
scitex-stats mcp list-tools -vv  # List tools with descriptions