io.github.inity13/decisionmatrix-mcp

up checked 2026-11-11T08:39:27.019Z

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Publisher-provided description

Deterministic multi-criteria decision analysis for AI agents — score, rank & explain options.

Summary by lookupd

Ranks options against weighted criteria with explained scores, head-to-head comparisons, and sensitivity tests of weight changes; no…

Install

Claude Code, remote (streamable-http)

claude mcp add --transport http decisionmatrix https://decisionmatrix-mcp.pages.dev/mcp

Claude Code, npm package (stdio)

claude mcp add decisionmatrix -- npx -y decisionmatrix-mcp

Codex, remote (streamable-http)

codex mcp add decisionmatrix --url https://decisionmatrix-mcp.pages.dev/mcp

Codex, npm package (stdio)

codex mcp add decisionmatrix -- npx -y decisionmatrix-mcp

Cursor, remote (streamable-http) → .cursor/mcp.json

{
  "mcpServers": {
    "decisionmatrix": {
      "url": "https://decisionmatrix-mcp.pages.dev/mcp"
    }
  }
}

Cursor, npm package (stdio) → .cursor/mcp.json

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

Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.

Tools (6 tools)

Publisher-provided text

create_decision Rank named options against weighted criteria and return the winner, full ranking, per-criterion score breakdowns, methodology, the weights used, and a plain-lan
score_options Score options against criteria when the score matrix is supplied separately. Returns the full normalized scored matrix (per-option, per-criterion) plus a rankin
sensitivity_analysis Test how robust the winner is to changes in criteria weights. Sweeps each criterion's weight +/- 'variation' (default 0.2 = 20%) over 'steps' (default 10) incre
compare_two Direct head-to-head comparison of exactly two options. Returns the winner, the score margin, how many criteria each option wins, and a per-criterion breakdown o
list_methods List the available scoring methods (weighted_sum, weighted_product, topsis) with descriptions, normalization details, score ranges, and when to use each. No par
health_check Server health, version, and capabilities. No parameters.

Details

Version: 1.0.2
Transports: streamable-http, stdio
Uptime (7 days): 100%
Median latency: 217 ms
First indexed: 2026-11-01T09:34:59.672Z
Last seen in registry: 2026-11-01T09:34:59.683Z
Repository: https://github.com/inity13/decisionmatrix-mcp

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