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avoid-ai-writing-mcp

by conorbronsdon
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    • slop-guard

      pedro0040
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables agents to score prose from 0-100 for formulaic AI writing tells using pure rule-based heuristics, exposing tools to analyze inline text or files on disk and return violation details, band labels, and concrete advice without any LLM judge or network calls.
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    • slop-guard

      Prawit65
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables agents to analyze inline prose or files on disk for formulaic AI writing patterns, returning a 0-100 score, band label, specific violations with context, and concrete advice. Uses purely programmatic, configurable rules with no LLM judge or API calls.
      -

    • slop-guard

      taichiwilson161
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables agents and users to analyze text or files for formulaic AI writing patterns and receive a 0–100 score, band label, violations with surrounding context, and concrete advice. It works programmatically without LLM judges or API calls.
      -

    • slop-guard

      YannisGreen055
      F
      license
      Not graded
      quality
      A
      maintenance
      Analyzes text and files for formulaic AI writing patterns, returning a 0-100 score, band label, specific violations with context, and concrete revision advice. Runs entirely locally with rule-based heuristics, requiring no LLM judge or API calls.
      -

    • slop-guard

      Horst53236
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables agents to score prose from 0–100 for formulaic AI writing patterns using rule-based linting, returning diagnostics such as band labels, violations with context, and advice. It can analyze inline text or files without API calls or LLM judges.
      -

    • slop-guard

      sofiawroblewski
      F
      license
      Not graded
      quality
      A
      maintenance
      Scores prose from 0 to 100 for formulaic AI writing patterns using purely programmatic rules, with no LLM judge or API calls. Enables agents to lint text or files and receive a score, band label, specific violations with surrounding context, and concrete advice for each hit.
      -
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.7/5.0

    Scored across 2 tools

    Disambiguation5/5

    score_text and audit_text have clearly separated purposes: one returns a compact classification while the other returns detailed flagged patterns and highlighted regions. The cross-references in the descriptions remove any real ambiguity about which tool to use.

    Naming Consistency5/5

    Both tool names follow the same verb_noun pattern with lowercase snake_case and concise action words. This is fully consistent and predictable.

    Tool Count4/5

    Two tools is slightly below the typical 3-15 range, but for a narrowly scoped local text detector the pair covers both a compact score and a detailed audit. Each tool has a distinct, useful role, so the small count feels intentional rather than inadequate.

    Completeness5/5

    The server's apparent domain is deterministic AI-writing detection on text, and the two tools cover the full user journey: getting a quick judgment or drilling into specific flagged patterns and highlighted regions. There are no obvious missing operations for this stated purpose.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

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