jev-mcp
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Alternatives to jev-mcp
No user-submitted related servers found.
Related Servers
- 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.5MIT
- 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.4MIT
- 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
- AlicenseNot gradedqualityCmaintenanceEnables coding agents to run source-bound evidence checks and bounded batch judgments for classification, extraction, and decision tasks via TypeSafe Jev.MIT
- AlicenseAqualityAmaintenanceEnables prototyping, running, and evaluating typed judgment questions against TypeSafe's Jev model, including accuracy, calibration, and threshold analysis.31MIT
- AlicenseNot gradedqualityBmaintenanceEnables MCP clients to consult TypeSafe's Jev through a judge tool, answering narrow typed questions with calibrated probabilities instead of prose.MIT
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.