A
licenseNot graded
qualityA
maintenanceMCP server offering text analysis tools for writing improvement, including spellcheck, readability, keyword analysis, passive voice detection, and AI-generated content detection.
10
MIT
Étincel MCP Server
by AIStoryHub
Related Servers
Alternatives to Étincel MCP Server
- FlicenseAqualityBmaintenanceContent writing toolkit for headline generation, readability scoring, tone analysis, outline building, and plagiarism similarity checking.561 PyPI-
- AlicenseAqualityBmaintenanceA private, open-source AI-text checker. Get a read on whether text looks AI-written, the exact AI-tell spans to fix, a reuse check, and a grammar pass.4MIT
- AlicenseAqualityBmaintenanceFlag AI tells, weasel words, passive voice, duplicate words, long sentences, nominalizations, hedging, and filler adverbs45MIT
- AlicenseAqualityAmaintenanceThree deterministic MCP tools that score text for AI-writing tells (em-dash density, hedge words, tricolons, boilerplate openers) and grade landing-page copy. No LLM, no network calls, no API key — same input always yields the same score. Published on the official MCP registry as io.github.parweb/ai-slop-checker.3MIT
Related Servers
- AlicenseBqualityAmaintenanceLocal-first toolkit with 16 tools for Chinese web-novel (网文) authors: style baselines, foreshadowing and plot-thread tracking, continuity & OOC audits, keyword and sentence-pattern analysis, and offline semantic search. No API key, no network — everything runs on your machine.218944 npm16MIT
- AlicenseAqualityCmaintenanceEnables editorial content QA over the Model Context Protocol with four local tools that analyze readability, AI-sounding language, SEO on-page factors, and produce full reports where every finding includes an actionable fix.41MIT
- AlicenseNot gradedqualityBmaintenanceEnables Claude to write in your personal style by learning from your local documents. It provides statistical style context for natural language rewriting, all without any data leaving your machine.MIT
- AlicenseAqualityBmaintenanceMCP server that analyzes your writing style to generate personal voice rules, scores drafts for AI slop, and verifies authorship, enabling LLMs to write in your specific voice.7MIT
- AlicenseAqualityCmaintenanceEnables detection and elimination of AI slop in text, providing tools to analyze writing for overused phrases, structural issues, and verbosity, and offers human writing rules tailored to context.32MIT
- AlicenseNot gradedqualityBmaintenanceProvides psycholinguistic, lexical, structural, and discourse-level rules to help writing sound human-authored. Includes reference readers and a compliance checker.MIT
TDQS
A4.4/5.0
Scored across 19 tools
Disambiguation5/5
Each tool targets a distinct resource and action: style lifecycle (list, get, create, update, delete, fork), voice checking (match, self-repetition), text auditing, dictionary management, and instructions. Even similar-sounding pairs like get_style_guide vs get_style_instructions are clearly differentiated by their descriptions.
Naming Consistency5/5
All 19 tools follow a consistent verb_noun snake_case pattern (list_styles, train_style, create_style_from_dials, check_voice_match, add_banned_word, etc.). There is no mixing of camelCase or inconsistent verb styles.
Tool Count4/5
With 19 tools, the set is on the heavier side but each tool serves a clear purpose within the server's broad scope of style management, auditing, and dictionary maintenance. The count is slightly over the ideal 3-15 range but still well-organized and justified.
Completeness5/5
The surface provides full lifecycle coverage for styles (create via samples or dials, read, update, delete, fork, list, set default), plus text quality checks (AI tells, voice match, self-repetition), word-list management, and instructions. There are no significant dead ends or missing core operations; the server intentionally does not generate prose directly.
Maintenance
ActivitySlowing
ResponsivenessNo issues