Jev MCP Server
Related Servers
Alternatives to Jev MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceEnables MCP clients to obtain typed, probabilistic decisions from text or structured state and up to four images—choosing among labeled options, scoring on ordered scales, and estimating whether propositions are true—for routing, triage, moderation, risk scoring, and similar agent workflows.50MIT
- AlicenseNot gradedqualityBmaintenanceEnables MCP clients to get machine-readable yes/no, choice, and score decisions from TypeSafe Jev, bridging fast classification to Cursor and other clients.MIT
- AlicenseAqualityCmaintenanceEnables MCP agents to evaluate content against typed questions (yes/no, choice, or score) in a single parallel call.130 npmApache 2.0
- AlicenseAqualityCmaintenanceLets MCP clients submit a situation and typed questions (yes/no, choice, or scale) to a decision model that returns calibrated probabilities plus an act-or-escalate flag. Enables agents to route, flag, approve, check, or rate cases and hand uncertain ones to a person.3334 npmApache 2.0
- AlicenseNot gradedqualityCmaintenanceEnables agents to evaluate single records or batches with dynamically authored typed questions, returning structured decisions and probabilities.25 PyPIMIT
- AlicenseNot gradedqualityCmaintenanceEnables structured yes/no, multiple-choice, and ordered-score judgments from supplied text and criteria, returning typed probabilities, selected labels, scores, and confidence. It exposes bounded decision tools without search, chat generation, arbitrary HTTP requests, or action execution.346 npmMIT
TDQS
Scored across 1 tool
There is only one tool, so an agent cannot confuse it with another tool. Its name and description clearly identify it as the evaluation entry point.
The sole tool uses a clear snake_case verb_noun convention ('jev_evaluate'), consistent with a single-tool surface. No conflicting naming patterns exist.
One tool is appropriate because the server is a focused wrapper around a single Jev evaluation operation. The tool is broad enough to handle classification, scoring, choice, and batch use cases, so additional tools would add little value.
For its stated scope—evaluating supplied text/JSON—the tool covers all core needs: multiple question types, batch evaluation, typed answers, confidence, and usage metadata. The explicit exclusions (fetching URLs, generating explanations) are outside the server's purpose, not missing features.