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Alternatives to jev-mcp

No user-submitted related servers found.

    Related Servers

    • A
      license
      A
      quality
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      maintenance
      Enables 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.
      5
      MIT
    • A
      license
      B
      quality
      C
      maintenance
      Enables 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.
      4
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables 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.
      7
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables prototyping, running, and evaluating typed judgment questions against TypeSafe's Jev model, including accuracy, calibration, and threshold analysis.
      3
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables MCP clients to consult TypeSafe's Jev through a judge tool, answering narrow typed questions with calibrated probabilities instead of prose.
      MIT

    TDQS

    B3.2/5.0

    Scored across 5 tools

    Disambiguation3/5

    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.

    Naming Consistency4/5

    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.

    Tool Count5/5

    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.

    Completeness4/5

    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.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues