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Related Servers

Alternatives to circe-mcp

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    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI hosts to check text for grammar, spelling, and style errors, measure readability, and generate tone-adjusted rewrites through structured tool calls. Every tool returns predictable, typed output for reliable routing and results.
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables agents to analyze text or files and score prose from 0–100 for formulaic AI writing patterns using rule-based heuristics, returning violations, band labels, and concrete advice.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables agents to analyze text or files and receive numeric slop scores, band labels, specific violations with context, and concrete writing advice, using rule-based diagnostics with no LLM judge or API calls.
      -
    • 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.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables agents to score prose from 0–100 for formulaic AI writing patterns using a purely rule-based linter, returning numeric scores, band labels, specific violations with context, and concrete advice. Also supports analyzing text files on disk directly.
      -
    • 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.
      -

    TDQS

    A4/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clearly distinct role: check_text finds violations, measure_text reports statistics with no verdict, fix_text applies safe fixes, list_rules enumerates rules, and explain_rule details a single rule. The check_text/measure_text boundary is explicitly clarified by 'no verdict' vs violation reporting, leaving no real overlap.

    Naming Consistency5/5

    All five tools follow a consistent verb_noun snake_case pattern (check_text, fix_text, measure_text, list_rules, explain_rule). Verb pairing with noun reads predictably across the set.

    Tool Count5/5

    Five tools is well-scoped for an editorial-linting server, covering the natural verbs (check, fix, measure, list, explain) without redundancy. Each tool earns its place in the workflow.

    Completeness4/5

    The core lifecycle is covered: discovery (list_rules, explain_rule), analysis (check_text, measure_text), and remediation (fix_text). Minor gaps exist, such as batch/file-level checking or rule configuration, but agents can work around them.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues