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Alternatives to jev-mcp

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    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
      9 npm
      MIT
    • A
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      quality
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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
      A
      quality
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      maintenance
      Enables AI coding agents to offload yes/no, multiple-choice, and scoring questions to TypeSafe's Jev, returning compact confidence-scored answers to save tokens and improve speed.
      1
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables any agent to ask typed questions (Noul, Choice, Score) against Jev's decision model and receive structured answers with probabilities, confidence, and an auditable act/review/abstain decision.
      53 npm
      1
      MIT
    • A
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      A
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      Enables AI coding agents to make fast, zero-output-token decisions by evaluating context, diffs, logs, or options through the OpenRouter Decisions API using TypeSafe Jev, returning calibrated probabilities for binary, categorical, or scoring questions.
      1
      32 npm
      3
      MIT

    TDQS

    A3.9/5.0

    Scored across 9 tools

    Disambiguation4/5

    Each tool has a clearly defined job—risk, classification, verification, review, screening, ranking—so they are mostly easy to distinguish. The main ambiguity is jev_evaluate, which is intentionally an escape hatch and can conceptually overlap with any of the other tools, though its description frames it as a fallback.

    Naming Consistency4/5

    All tools share the jev_ prefix and use snake_case, making the set feel consistent. The only deviation is jev_coding_loop, which is a noun-style name rather than a verb_noun pattern like assess_change_risk or classify_issue.

    Tool Count5/5

    Nine tools is well-scoped for a decision-support/evaluation server. Each tool addresses a distinct stage in the workflow—screening, risk assessment, review, verification, ranking, and a general escape hatch—so none feels redundant or excessive.

    Completeness5/5

    The tool surface covers the full evaluation lifecycle for the stated domain: risk assessment, issue classification, requirement checking, coding-loop guidance, diff review, claim verification, text screening, and ranking. The escape-hatch jev_evaluate also prevents dead ends for questions that don't fit an existing recipe.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues