kev-decision-mcp
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- AlicenseNot gradedqualityAmaintenanceExposes three stdio tools (jev_ask, jev_rank, jev_check) that return typed judgments—yes/no, choice, and score answers with calibrated probabilities—instead of prose. It runs on an offline mock by default, resolving a live TypeSafe or OpenRouter credential only when configured, and reports all egress on stderr.66 npmApache 2.0
- AlicenseNot gradedqualityAmaintenanceExposes three stdio tools that answer typed questions — noul (yes/no), choice, and score — with calibrated probabilities instead of prose, running fully offline on a synthetic mock unless a live credential is explicitly supplied.66 npmApache 2.0

faraztools-mcpofficial
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TDQS
Scored across 4 tools
Each tool has a distinct purpose: listing models, standard evaluation, order-sensitivity testing, and packed-vs-separate comparison. The three evaluation tools share a common foundation but are clearly differentiated by their constraints and outputs, though they could still be confused without careful reading.
All tools follow a consistent kev_<verb> snake_case pattern, making the set predictable and uniform. The verbs (list, evaluate, permute, separate) are domain-specific but consistently applied.
Four tools is well-scoped for a decision evaluation server. Each tool adds a distinct capability—model discovery, packed evaluation, order sensitivity, and independent evaluation—without redundancy or bloat.
The decision evaluation domain is fully covered: model metadata, packed evaluation supporting multiple question types, order-sensitivity checking, and independent evaluation for comparison. There are no obvious missing operations or dead ends for the stated purpose.