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Alternatives to jev-eval-mcp

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    • A
      license
      B
      quality
      C
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      Enables AI agents to obtain typed judgments from TypeSafe's Jev System One models, including yes/no probabilities, multiple-choice selections with distributions, and rubric-based scores, directly usable in code.
      5
      2
      AGPL 3.0
    • 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.
      27 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables MCP-capable agents to run TypeSafe's Jev judgment model as typed yes/no, choice, and score tools, with calibrated probabilities, confidence thresholds, escalation for uncertain or non-judgment tasks, and an optional action gate that fails open.
      1
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP clients to submit bounded semantic-uncertainty judgments to the pinned TypeSafe Jev API, with tools for yes/no, choice, and score evaluations plus optional evidence or context selection.
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables MCP clients to call TypeSafe's JEV classifier and receive structured, typed judgments with probabilities for binary, choice, and scoring questions.
      1
      7
      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

    TDQS

    A4.1/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: jev_map judges items in a list, jev_eval evaluates question wordings against labeled data, and jev_ask runs questions to see answers. There is no overlap or ambiguity in their intended use cases.

    Naming Consistency5/5

    All tools share the 'jev_' prefix and use a consistent verb_noun pattern: map, eval, ask. The naming is predictable and clearly indicates the action each tool performs.

    Tool Count4/5

    With only 3 tools, the server is on the low end of the appropriate range, but each tool covers a distinct phase of the evaluation workflow (prototype, evaluate, triage). The count is reasonable for the narrow domain and does not feel artificially padded.

    Completeness4/5

    The tools cover the core lifecycle for question evaluation: jev_ask for prototyping, jev_eval for validating wording, and jev_map for applying judgments at scale. Minor gaps exist (e.g., no tool for managing question sets or exporting results), but these are not blocking for the primary workflow.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive