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Alternatives to jev-mcp

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to submit a state and typed questions and receive structured judgments such as yes/no probabilities, named choices, and rubric scores, with no text generation or parsing.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables 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 npm
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables agents to evaluate single records or batches with dynamically authored typed questions, returning structured decisions and probabilities.
      25 PyPI
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI assistants to obtain calibrated probabilities, option picks, scale scores, and multi-question judgments for batches of short text, returning numeric results for sorting, filtering, and counting.
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables 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.
      5
      0
      MIT

    TDQS

    A3.8/5.0

    Scored across 7 tools

    Disambiguation4/5

    Each tool maps to a distinct judgment mode: open typed judgment, closed-list classification, ordered scoring, yes/no checking, candidate matching, text screening, and health inspection. The generic jev_ask could broadly overlap with the more specific modes, but the descriptions clarify when each should be used.

    Naming Consistency5/5

    All tools share the consistent jev_ prefix and use short lowercase names matching their action or purpose. The naming convention is uniform and predictable across the entire set.

    Tool Count5/5

    Seven tools is a well-scoped set for a single Jev judgment API. Each tool covers a distinct operation without redundancy, and the count feels neither thin nor bloated.

    Completeness5/5

    The tool surface covers the core judgment types Jev appears to support: ask, classify, score, check, match, and screen, plus health for configuration introspection. The repeated exclusions of text generation and numeric extraction indicate those are intentionally out of scope rather than missing.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive