jev-mcp
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- AlicenseAqualityCmaintenanceEnables coding or reasoning agents to request structured judgments from TypeSafe's Jev model at decision points, including choices, scores, claim verification, and code reviews, with probabilities and confidence returned as data.59 npmMIT
- AlicenseBqualityCmaintenanceEnables AI agent skills to route state-evaluation requests to TypeSafe AI's Jev System One model, supporting typed questions, choice classification, binary probabilities, and rubric scoring with calibrated confidence.42MIT
- AlicenseAqualityBmaintenanceEnables AI coding agents to offload yes/no, multiple-choice, and scoring questions to TypeSafe's Jev, returning compact confidence-scored answers to save tokens and improve speed.1MIT
- AlicenseAqualityBmaintenanceEnables frontier coding agents to delegate routine probabilistic judgments to TypeSafe Jev, providing calibrated triage signals for failures, attempts, completion, context ranking, findings, risk, and generic evidence-grounded questions.7MIT
- FlicenseNot gradedqualityBmaintenanceEnables Claude Code agents to perform structured decision-making through TypeSafe Jev, supporting yes/no checks, route selection, scoring, and batched multi-question judgments with confidence values.1-
- AlicenseNot gradedqualityAmaintenanceEnables Claude Code or any MCP client to ask TypeSafe's Jev for calibrated, typed judgments (probabilities, choices, scores) instead of prose, with local caching and cost tracking.1MIT
TDQS
Scored across 5 tools
jev_evaluate subsumes the other evaluation tools, creating potential overlap. The descriptions clarify that evaluate is for batched/mixed types while the specialized tools handle single questions, but an agent could still be unsure which to use for a one-off noul or choice query.
All tools share the 'jev_' prefix in lowercase snake_case, making them easily recognizable as a family. The names mix verbs and nouns (evaluate, models vs noul, choice, score), but the uniform prefix and short, predictable tokens keep the pattern strong.
Five tools is a well-scoped size for an evaluation API wrapper. It includes a general evaluator, three specialized question types, and a model discovery utility without unnecessary bloat.
The toolset covers all declared question types (noul, choice, score) and provides the necessary model listing capability. It lacks history or configuration management, but those are not implied by the server's focused purpose.