Jev MCP Server
Related Servers
Alternatives to Jev MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceEnables agents to evaluate single records or batches with dynamically authored typed questions, returning structured decisions and probabilities.MIT
- AlicenseAqualityCmaintenanceEnables agents to perform typed judgments—classify, score, check, match, and screen—over closed answer sets with confidence scores, without text generation.74MIT
- AlicenseNot gradedqualityCmaintenanceEnables MCP clients to call TypeSafe's JEV classifier and receive structured, typed judgments with probabilities for binary, choice, and scoring questions.MIT
- AlicenseNot gradedqualityAmaintenanceEnables MCP clients to hand fast, no-text-output decisions to Jev, reducing latency and token usage while escalating uncertain cases back to the LLM.5MIT
- AlicenseNot gradedqualityBmaintenanceProvides MCP clients a single decision-only tool to classify prompts as safe for local or cloud models, or as containing PII or jailbreak content, without executing actions or calling AI models.18 npmCryptographic Autonomy 1.0 (Combined Work Exception)
- AlicenseAqualityBmaintenanceProvides MCP tools for lead qualification, enabling evidence gathering from CRM, scoring, and knowledge base with role-based access and deterministic decision gating.4AGPL 3.0
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.