ConKurrence

One command. Find out if your AI agrees with itself.

ConKurrence is a statistically validated consensus measurement toolkit for AI evaluation pipelines. It uses multiple AI models as independent raters, measures inter-rater reliability with Fleiss' kappa and bootstrap confidence intervals, and routes contested items to human experts.

Install

npm install -g conkurrence

MCP Server

Use ConKurrence as an MCP server in Claude Desktop or any MCP-compatible client:

npx conkurrence mcp

Claude Desktop Configuration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "conkurrence": {
      "command": "npx",
      "args": ["-y", "conkurrence", "mcp"]
    }
  }
}

Claude Code Plugin

/plugin marketplace add AlligatorC0der/conkurrence

Features

• Multi-model evaluation — Run your schema against Bedrock, OpenAI, and Gemini models simultaneously
• Statistical rigor — Fleiss' kappa with bootstrap confidence intervals, Kendall's W for validity
• Self-consistency mode — No API keys needed; uses the host model via MCP Sampling
• Schema suggestion — AI-powered schema design from your data
• Trend tracking — Compare runs over time, detect agreement degradation
• Cost estimation — Know the cost before running

MCP Tools

Tool	Description
conkurrence_run	Execute an evaluation across multiple AI raters
conkurrence_report	Generate a detailed markdown report
conkurrence_compare	Side-by-side comparison of two runs
conkurrence_trend	Track agreement over multiple runs
conkurrence_suggest	AI-powered schema suggestion from your data
conkurrence_validate_schema	Validate a schema before running
conkurrence_estimate	Estimate cost and token usage

Links

• Homepage: conkurrence.com
• npm: npmjs.com/package/conkurrence
• Terms of Service: app.conkurrence.com/terms
• Privacy Policy: app.conkurrence.com/privacy

License

BUSL-1.1 — Business Source License 1.1