Étincel MCP Server
The Étincel MCP Server helps shape AI-assisted non-fiction prose into more human-sounding text by managing writing styles, auditing for AI tells, and maintaining custom rules. Key capabilities:
Style Management: List, create, train, fork, update, delete, and set default styles (presets, trained voices, or team styles). Train a voice from writing samples (rhythm, contractions, em-dash habits, etc.) or build one manually via 11 explicit dials.
Voice & Rhythm Checking: Compare a draft’s rhythm to a trained voice baseline and detect self-repetition patterns across the author’s past work.
Text Auditing: Deterministically scan for AI-writing tells (banned words, structural patterns) with severity tiers and strengths signal, optionally per register.
Custom Vocabulary: Add or remove banned and allowed words globally or per style; view effective merged lists.
Custom Drafting Instructions: Set, clear, and retrieve free-text drafting rules scoped globally or per style.
Integration: Operates as an MCP server for Claude Code/Desktop, with a CLI and CI/CD integrations.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Étincel MCP ServerAudit my draft for AI tells and show me the findings."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Étincel: Non-Fiction Writing Connector
___ ___ ___ ___ ___ ___
/\ \ /\ \ ___ /\__\ /\ \ /\ \ /\__\
/::\ \ \:\ \ /\ \ /::| | /::\ \ /::\ \ /:/ /
/:/\:\ \ \:\ \ \:\ \ /:|:| | /:/\:\ \ /:/\:\ \ /:/ /
/::\~\:\ \ /::\ \ /::\__\ /:/|:| |__ /:/ \:\ \ /::\~\:\ \ /:/ /
/:/\:\ \:\__\ /:/\:\__\ __/:/\/__/ /:/ |:| /\__\ /:/__/ \:\__\ /:/\:\ \:\__\ /:/__/
\:\~\:\ \/__/ /:/ \/__/ /\/:/ / \/__|:|/:/ / \:\ \ \/__/ \:\~\:\ \/__/ \:\ \
\:\ \:\__\ /:/ / \::/__/ |:/:/ / \:\ \ \:\ \:\__\ \:\ \
\:\ \/__/ \/__/ \:\__\ |::/ / \:\ \ \:\ \/__/ \:\ \
\:\__\ \/__/ /:/ / \:\__\ \:\__\ \:\__\
\/__/ \/__/ \/__/ \/__/ \/__/
This audits the hosted remote server (etincel.ai/api/mcp), not the local/stdio engine in this repo; the two expose the same tools but run as separate deployments.
A connector for Claude Code, Claude Desktop, and any MCP-enabled tool that adds a layer of human-like non-fiction authoring on top of whatever you already write in. It does not replace your email client, editor, or CMS. It shapes the prose before it gets there, in a voice you either train from your own writing or pick from a set of premade emotional-tone presets, and it flags AI writing tells transparently instead of silently rewriting your words.
Why
AI-drafted prose has a recognizable shape: uniform paragraphs, hedged authority, em dashes where a comma would do, case studies with no flaws, closings that resolve too neatly. That shape is what makes text feel AI-written even when it's factually fine. This connector encodes the rules that avoid that shape, and, just as important, it shows you what it found and why, instead of quietly overwriting your voice. You stay the author.
Related MCP server: my-voice-mcp
What's in here
An MCP server (
src/server.ts) exposing nineteen tools:list_styles: premade tone presets, any voices you've trained, and (if a repo-local.etincelrcdefines one) a shared team styleget_style_guide: the drafting instructions for one styletrain_style: learn a voice from your own writing samples (sentence rhythm, contraction rate, em-dash habits, paragraph variance, recurring phrasing: measured, not guessed)create_style_from_dials: build a style from explicit formality/warmth/directness and mechanical dials instead of samplesupdate_style: rename a trained voice or adjust its dials in placefork_style: copy a preset's dials and guide into a new trained voice you can retrain or hand-tune, or fork another installer's style once they've published it publicly on the hosted gallery (addressed ashandle/slug, e.g.jpleblanc/blunt-memo, the same address shown on its public page atetincel.ai/v/handle/slug); a public-style fork makes one network call toetincel.aito fetch it, a preset fork never leaves this installdelete_style: permanently remove a trained voiceset_default_style: remember which style to use without repeating yourselfcheck_voice_match: compare a draft's measured rhythm against a trained voice's baseline. A rhythm/mechanics check, not an authorship or AI-detection check, and low-confidence on short inputcheck_self_repetition: compare a draft against a voice's own recent training samples for habits, not AI tells: the same opener, or a phrase, recurring across several past pieces ("you've opened this way in 4 of your last 6 pieces"). Local install only for nowaudit_text: a deterministic, rules-based scan for AI tells, returning a tier, specific findings with severity, and a strengths signal (specificity, concrete-vs-abstract ratio, sentence-rhythm variation) so fixes don't flatten the prose. Takes an optionalregister(email/blog/memo/essay/social/docs/general, defaultgeneral) to calibrate strictness against the kind of text it is:docssuppresses Markdown-structure false positives (headings, bolded terms) and recalibrates rhythm/vocabulary detection against long-form reference prose instead of punchier short-form copyadd_banned_word/remove_banned_word: maintain your own banned-vocabulary list, checked byaudit_textalongside the built-in corpusadd_custom_word/remove_custom_word: maintain a "never flag this" list: an org's own acronyms or house terms, the corporate-dictionary caselist_dictionary: see a scope's banned/custom words, and (for a style) what actually applies once merged with the global listset_style_instructions/clear_style_instructions/get_style_instructions: save, remove, or read free-text drafting rules for a scope (required elements, forbidden topics, format constraints), merged intoget_style_guidethe same way dictionaries merge intoaudit_text
A Claude Code / Claude Desktop skill (
skills/etincel-nonfiction/) that uses those tools when you're drafting or revising non-fiction prose of any meaningful length.
Trained voices, dictionaries, and your default style live locally in ~/.etincel/: nothing is sent anywhere. audit_text is plain deterministic code (string analysis + a curated corpus of AI-writing tells), not a model call. The one exception is forking a public style via fork_style, which fetches (never sends) that style's guide from etincel.ai's public gallery; forking a preset, or anything else in this list, still touches the network not at all.
Custom dictionaries
Beyond the built-in AI-tell corpus, you can maintain your own banned and "always allowed" word lists: just tell Claude (or any MCP client) things like "add [word] to my banned words list" or "add [word] to my custom words list, it's one of ours." Each list lives at a scope: global (applies everywhere, the default when no style is named) or a specific style id, whose list is merged on top of global when you audit against that style. list_dictionary shows what's saved for a scope, plus the effective merged list for a style. Editing the global list is already the way to keep a word in sync across every style: it's merged in automatically, live, every time audit_text or list_dictionary runs.
Install
Claude Code
/plugin marketplace add AIStoryHub/etincel
/plugin install etincel-nonfictionOr from a local clone: /plugin marketplace add /path/to/etincel.
Claude Desktop / other MCP hosts
Point your MCP config at the built server:
{
"mcpServers": {
"etincel-nonfiction": {
"command": "node",
"args": ["/path/to/etincel/dist/server.js"]
}
}
}Build first: npm install && npm run build.
Remote (hosted, multi-tenant)
A hosted version is also available at https://etincel.ai/api/mcp, exposing
the same tools over Streamable HTTP with per-account auth instead of stdio.
Point any MCP client at it directly:
{
"mcpServers": {
"etincel-nonfiction": {
"url": "https://etincel.ai/api/mcp"
}
}
}The hosted server isn't part of this repo; this repo is the local/stdio engine, CLI, and skill that the hosted version is built on top of.
Using it
Once installed, just ask for what you'd normally ask for, like "draft an email to the team about the delay," "write a blog post about X," or "clean up this memo," inside Claude Code or Claude Desktop. The skill picks up automatically for non-fiction prose of meaningful length. To train your own voice:
Train a style called "me" from these three emails I wrote: [paste samples]
Then either name it per-request ("write this in my voice") or set it as default:
Set my default style to "me"
Style presets
Twelve premade presets ship out of the box: six emotional tones (Direct & Warm, Executive Brief, Reflective Essayist, Founder Memo, Plainspoken Analyst, Wry & Candid) plus six use-case presets (PR Review, Code Comment, Slack Message, LinkedIn Post, Website Copy, Blog Post). Each carries formality/warmth/directness dials plus a sentence-rhythm and voice description that gets fed to the model as drafting context, not a template that fills in blanks. The server reads these from src/data/presets.json. Fork any preset into a trained voice with fork_style to make it your own.
Command-line lint
audit_text is a pure function under the hood, so it also ships as a CLI, for linting prose outside a chat client (READMEs, docs, PR descriptions in CI):
npx etincel lint 'docs/**/*.md'
npx etincel lint README.md --register docs --threshold yellowExits non-zero if any matched file's tier is at or above --threshold (default orange). .md/.mdx files default to the docs register automatically (suppresses the Markdown-structure false positives, since a real heading isn't a chatbot tell); pass --register to override. Add --json for a machine-readable report. Run npx etincel lint --help for the full option list.
A GitHub Action wraps the same CLI (see action.yml, and .github/workflows/lint.yml in this repo for a working example):
- uses: AIStoryHub/etincel@main
with:
patterns: "docs/**/*.md README.md"
threshold: orangeA CircleCI orb wraps the same CLI (see orb.yml, and .circleci/config.yml in this repo for a working example). Once it's published to the CircleCI Orb Registry, usage will look like:
version: 2.1
orbs:
etincel: aistoryhub/etincel@1.0.0
workflows:
lint:
jobs:
- etincel/lint:
patterns: "docs/**/*.md README.md"
threshold: orangeIt isn't published yet. Until then, copy the commands.lint and jobs.lint blocks from orb.yml into your own .circleci/config.yml.
Repo-local config: dictionary, instructions, and a shared team style
A team's rules don't have to live only in each person's local ~/.etincel/. Drop a .etincelrc (or .etincelrc.json / etincel.config.json) at the repo root and it's picked up automatically by the CLI and by the local (stdio) server, reviewable in code review and versioned instead of invisible and gone when someone leaves:
{
"bannedWords": ["Acme Cloud Platform"],
"allowedWords": ["leverage"],
"register": "docs",
"threshold": "orange",
"instructions": "Always include a one-line CTA at the end.",
"style": {
"name": "House Voice",
"dials": {
"formality": 6,
"warmth": 4,
"directness": 7,
"sentenceLength": 40,
"sentenceRhythmVariance": 50,
"paragraphVariance": 30,
"contractionUse": 20,
"emDashUse": 0,
"fragmentTolerance": 10,
"questionUse": 5,
"entropy": 60
}
}
}bannedWords/allowedWordsmerge alongside whatever's in your account/style dictionary;register/thresholdact as repo-wide defaults that an explicit--register/--thresholdflag still overrides.instructionsis free text, folded intoget_style_guide'sinstructionsfor every style, not just the team one, ahead of your own account-level global instructions: the team-wide equivalent ofset_style_instructionswith nostyleId, but committed to the repo instead of living in one person's account.styledefines a shared "house voice" from dials, addressable everywhere asstyleId: "team"(get_style_guide, and once forked into a real trained voice withfork_style, everywhere else too) so a team has one already-tuned starting voice from day one instead of everyone hand-training or hand-tuning their own from scratch.list_stylesincludes it automatically when a.etincelrcin the current repo defines one.
The hosted server doesn't use any of this (it has no local repo to look in).
Sharing config across a team without committing it
.etincelrc is the versioned, code-reviewable layer above; the layer beneath it is ETINCEL_HOME, an environment variable that points the local (stdio) server and CLI at a directory to use instead of the default ~/.etincel/. Point every teammate's ETINCEL_HOME at the same shared, synced, or mounted directory (a repo-external path everyone's machine can read, e.g. something synced by your usual file-sharing setup) and trained voices, the default style, and account-level instructions/dictionaries are shared too, not just the .etincelrc-committed subset:
{
"mcpServers": {
"etincel-nonfiction": {
"command": "node",
"args": ["/path/to/etincel/dist/server.js"],
"env": { "ETINCEL_HOME": "/path/to/shared/etincel-home" }
}
}
}Nothing else to export or import: pointing ETINCEL_HOME at the same directory is the sync, the same way it already is for a single person's ~/.etincel/.
Development
npm install
npm test # run the engine/tools test suite (node:test via tsx)
npm run dev # run the MCP server over stdio via tsx, for local testing
npm run build # compile to dist/Status
Early. The audit corpus (src/data/) is a curated subset, not exhaustive: see src/data/SOURCES.md for provenance and what's not yet ported.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- Alicense-quality-maintenanceProvides tools and resources to detect AI-generated writing patterns and refine text for more authentic, human-like communication. It enables users to analyze phrasing via a scoring system and apply conversational guides tailored for platforms like Twitter and LinkedIn.1
- Flicense-qualityCmaintenanceA local-first MCP server that builds compact voice profiles from writing samples, then compares, rewrites, or generates new text in that voice.
- Alicense-qualityCmaintenanceEnables 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
- Alicense-qualityDmaintenanceEnables 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.2MIT
Related MCP Connectors
Loads your personal writing voice into any AI and scores how closely a draft matches it.
A personal RAG database you build from chat, so AI creates work that sounds like you.
Prose linter + AI-slop detector: weasel words, passive voice, hedging, and research-cited AI tells
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/AIStoryHub/etincel'
If you have feedback or need assistance with the MCP directory API, please join our Discord server