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PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Etincel Nonfiction

作者:AIStoryHub版本 0.10.1i★ 9i电脑或云端
注册名称ai.etincel/etincel-nonfiction

安装方法

What it does

Trainable non-fiction writing voice, presets, and an anti-AI-tells audit for Claude, via MCP.

  • Connects 电脑或云端
  • Account or key Cloud: Sign in to the service when you connect (OAuth) · Local: No key needed
  • Category 其他

安装

选择你使用的 AI 应用,然后复制设置。

通过 5/5 项检查 · 你的提问会经过开发者的服务器(etincel.ai)

第一步:你用哪个 AI?

选择你用的应用,步骤会显示在下方。

可连接 Claude · 约 2 分钟

不需要密钥,不用安装程序 · 在 claude.ai 或桌面应用设置一次,即可在聊天中使用 · 免费账户可添加 1 个

  1. 打开 Claude 的 Connectors 页面

    CustomizeConnectors

    CustomizeConnectors1+ Add2https://…3Add4
  2. 点击“+ Add” → “Add custom connector”,填写这 2 项

    把这里的内容复制到 Claude 中同名的输入框,然后点击 Continue

    Name · 名称Etincel Nonfiction
    Remote MCP server URL · 地址https://etincel.ai/api/mcp

    Authentication 保持 Claude 检测到的设置,然后点击 Add

  3. 在聊天中开启

    +ConnectorsEtincel Nonfiction

  4. 试一试

    用 Etincel Nonfiction 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Claude 说正在使用 Etincel Nonfiction,或回答中出现 Etincel Nonfiction 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同

仅企业版 ChatGPT 可连接

适用于网页版 ChatGPT Business、Enterprise 或 Edu,需由工作区管理员或所有者添加 · 使用 Free、Plus 或 Pro:你的 ChatGPT 方案暂时无法自行连接 MCP

  1. 在网页版 ChatGPT 打开添加 MCP 的页面

    Plugins+Add custom MCP server

    ChatGPTPlugins1+2https://…3Create4
  2. 填写名称和地址

    输入名称,在 Connection 下粘贴地址,勾选风险提示,然后点击 Create as a plugin

    Name · 名称Etincel Nonfiction
    Connection · 地址https://etincel.ai/api/mcp
  3. 在聊天中选择 Etincel Nonfiction

    开启新聊天,输入前先从插件列表中选择 Etincel Nonfiction

  4. 试一试

    用 Etincel Nonfiction 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 ChatGPT 说正在使用 Etincel Nonfiction,或回答中出现 Etincel Nonfiction 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 OpenAI 帮助页面核实 · 你的界面可能因版本略有不同

可连接 Claude Code · 约 2 分钟

不需要密钥,不用安装程序

  1. 打开终端

    Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell

  2. 粘贴这条命令并按 Enter

    claude mcp add --transport http etincel-nonfiction https://etincel.ai/api/mcp
  3. 在 Claude Code 中输入 /mcp

    应能看到 Etincel Nonfiction 在列表中并显示已连接

  4. 试一试

    用 Etincel Nonfiction 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Claude Code 说正在使用 Etincel Nonfiction,或回答中出现 Etincel Nonfiction 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同

可连接 Cursor · 约 2 分钟

不需要密钥,不用安装程序

  1. 点击这个按钮打开 Cursor

    在 Cursor 中打开

    Cursor 会请你确认安装,点击 Install

  2. 在 Cursor 中以 Agent 模式打开 AI 聊天

  3. 试一试

    用 Etincel Nonfiction 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Cursor 说正在使用 Etincel Nonfiction,或回答中出现 Etincel Nonfiction 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同

可连接 VS Code · 约 2 分钟

不需要密钥,不用安装程序

  1. 点击这个按钮打开 VS Code

    在 VS Code 中打开

    VS Code 会请你确认安装,点击 Install

  2. 在 VS Code 中以 Agent 模式打开 AI 聊天

  3. 试一试

    用 Etincel Nonfiction 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 VS Code 说正在使用 Etincel Nonfiction,或回答中出现 Etincel Nonfiction 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同

其他支持 MCP 的应用(如 Windsurf、Zed、Gemini CLI)添加方式各不相同,请在应用列表中查看

查看所有支持 MCP 的应用 →

通过网页连接的应用使用的地址

地址https://etincel.ai/api/mcp

JSON 设置在下方“开发者专用”中

卡住了?问问正在用 Etincel Nonfiction 的人💬 讨论 →
开发者专用:终端命令和 JSON 设置

通过网页连接

Claude Code

claude mcp add --transport http etincel-nonfiction https://etincel.ai/api/mcp

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "etincel-nonfiction": {
      "url": "https://etincel.ai/api/mcp"
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "etincel-nonfiction": {
      "type": "http",
      "url": "https://etincel.ai/api/mcp"
    }
  }
}

安装在电脑上

Claude Code

claude mcp add etincel-nonfiction -- npx -y etincel serve

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "etincel-nonfiction": {
      "command": "npx",
      "args": [
        "-y",
        "etincel",
        "serve"
      ]
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "etincel-nonfiction": {
      "command": "npx",
      "args": [
        "-y",
        "etincel",
        "serve"
      ]
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "etincel-nonfiction": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "etincel",
        "serve"
      ]
    }
  }
}

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

一览

每周下载量i
125/周
已验证域名
✓ etincel.ai
连接方式
电脑或云端
传输方式
stdio, streamable-http
最新版本i
0.10.1
分类i
其他
发布到注册中心i
2026年8月15日
代码最后更新i
2026年8月15日
作者
AIStoryHub
软件包
npm: etincel
注册状态
活跃

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。

通过互联网连接,适用于

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

在你的电脑上运行,适用于

ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast

全部应用及其优缺点 →

它能做什么

服务器要求先登录,才会列出它的工具。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月12日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 etincel.ai 验证(注册中心会核实域名所有权)

  • ✓ 通过

    仍在维护

    代码最后更新于3个月前

  • ✓ 通过

    有许可证

    使用 MIT

  • ✓ 通过

    端点有响应

    在 163 毫秒内响应(HTTP 401)

  • ✓ 通过

    使用 OAuth 登录

    声明支持 OAuth 登录,你的 AI 应用可以带你去登录

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

讨论

提问、分享技巧或报告无法使用。按“有帮助”数量排序。

还没有帖子,欢迎第一个提问或分享。

此处内容由用户撰写,不代表 PopNx 团队。

使用 Google 登录后发帖

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与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 19293 个服务器的 96%
  • 发布到注册中心的时间比此分类中其他 19293 个服务器的 20% 更新
  • 基础检查结果等于或优于此分类中其他 19293 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Etincel Nonfiction 安全吗?

它在 5 项适用的基础检查中通过了 5 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于3个月前,最新版本(0.10.1)于3个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,因此也能用于支持远程 MCP 的应用,例如 ChatGPT Business 及以上方案。

有什么可以替代它?

同一分类中有:World Monitor, Claude Flow, Tldraw

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

World Monitor

Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.

作者:koala73广泛使用★ 9万今天更新

在云端运行✓ 服务方 · worldmonitor.app

Claude Flow

AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.

作者:ruvnet广泛使用↓ 1.4万/周★ 8.1万14个月前更新

在你的电脑上运行

Tldraw

Draw and visually collaborate with your agents on tldraw's canvas.

作者:tldraw广泛使用★ 5.1万8个月前更新

在云端运行

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Étincel: Non-Fiction Writing Connector

      ___           ___                       ___           ___           ___           ___

/\ \ /\ \ _ /\\ /\ \ /\ \ /\\ /::\ \ \:\ \ /\ \ /::| | /::\ \ /::\ \ /:/ / /:/\:\ \ \:\ \ \:\ \ /:|:| | /:/\:\ \ /:/\:\ \ /:/ / /::\~\:\ \ /::\ \ /::\\ /:/|:| | /:/ \:\ \ /::\~\:\ \ /:/ / /:/\:\ \:\\ /:/\:\\ /:/\// /:/ |:| /\\ /:// \:\\ /:/\:\ \:\\ /:// \:\~\:\ \// /:/ \// /\/:/ / \/|:|/:/ / \:\ \ \// \:\~\:\ \// \:\ \ \:\ \:\\ /:/ / \::// |:/:/ / \:\ \ \:\ \:\\ \:\ \ \:\ \// \// \:\\ |::/ / \:\ \ \:\ \// \:\ \ \:\\ \// /:/ / \:\\ \:\\ \:\\ \// \// \// \// \//

Find the AI tells in your prose. Deterministically, locally, in CI.

npx etincel lint README.md

No install, no account, no model call, no network.

$ npx etincel lint drafts/announcement.md --register blog

✗ drafts/announcement.md RED 100/100 (8 findings, 169 words, register: blog) Heavy AI styling. Multiple strong tells stacking up, worth a structural rewrite, not a word-swap pass.

Whole-piece rhythm medium uniform-paragraph-length 6 paragraphs, most running about the same length with little variation between them. Vary paragraph length more. medium low-burstiness 13 sentences averaging 13 words, with little variation in length from one sentence to the next. Mix short sentences with long; allow fragments. medium mechanical-register-drift Fragment rate and structural variety (sentence openers, punctuation mix) sit off where blog prose typically lands. Allow more sentence fragments and vary openers/punctuation more.

Vocabulary and phrasing high comprehensive L3:C30 → thorough, complete high cutting-edge L3:C109 → newest, latest high leverage L3:C99 → use high seamless L3:C150 → smooth, easy high streamline L3:C70 → simplify, speed up

strengths specificity 11.4/1k · concrete:abstract 0.40 · burstiness 0.32

1 file audited, 1 at or above orange.

Étincel is two things. A deterministic audit that finds the patterns making prose read as machine-written, as a CLI, a GitHub Action, and an MCP tool. And a voice layer that trains Claude, Cursor, or any MCP client to draft in a style measured from your own writing, so the problem is smaller before you ever read the draft.

AI-drafted prose has a recognizable shape: uniform paragraphs, hedged authority, em dashes where a comma would do, closings that resolve too neatly. Étincel encodes the rules against that shape and, just as important, shows you what it found and why instead of quietly overwriting your voice. There is no model call anywhere in the audit path, and you decide what changes. You stay the author.

Does it work?

We measure it rather than assert it. Pooled AUC per register, measured by assay against labeled corpora with a fixed bootstrap seed, so any PR that drops these numbers fails CI:

RegisterAUC
memo0.909
essay0.900
blog0.820
general0.748
docs0.735
email0.540

Email is close to a coin flip. It's deliberately uncalibrated, and we track it anyway so an accidental regression doesn't go unnoticed. general is uncalibrated too. The calibrated registers are docs, blog, memo, and essay; use those if the number matters to you. See efficacy-baselines.json and src/data/SOURCES.md for method and provenance.

How this compares

vs. [Vale](https://vale.sh) + [vale-ai-tells](https://github.com/tbhb/vale-ai-tells) Vale is an excellent markup-aware linter and vale-ai-tells is a serious 78-rule package. They match tokens against patterns. Étincel measures shape: sentence-rhythm variance, paragraph-length uniformity, and repetition against your own previous drafts, the kind of statistical layer vale-ai-tells' own README says needs analysis beyond what token matching can do. Étincel also feeds a trained voice to the model before you draft, which no linter does. Running both is reasonable; they overlap less than you'd expect.

vs. skill files (stop-slop, avoid-ai-writing, no-slop) Those are instructions to a model, and they help. But a prompt can't verify it worked, can't produce an exit code, and can't gate a merge. Use one *and* run this in CI.

vs. humanizers (Undetectable.ai, QuillBot, StealthWriter) Those rewrite your text to evade detectors. Turnitin now has a dedicated AI-paraphrasing detection feature, expanded in 2025 to target humanizer output specifically. Étincel does the opposite job: it never modifies your text, and it would be a poor tool for fooling anyone.

vs. detectors (GPTZero, Pangram, Originality.ai, Copyleaks) Those answer "was a machine involved?" with a probability, over a whole document, as a verdict on authorship, in the cloud. Étincel answers "which specific patterns make this read as machine-written?" with locations and severities, locally, and never renders a verdict on who wrote something.

Install

Also listed on the official MCP registry as ai.etincel/etincel-nonfiction, so MCP-aware clients that auto-discover servers from there (VS Code's @mcp gallery, for one) find it without any of the config below.

Claude Code
/plugin marketplace add AIStoryHub/etincel

/plugin install etincel-nonfiction

Or from a local clone: /plugin marketplace add /path/to/etincel.

Claude Desktop / other MCP hosts
{

"mcpServers": { "etincel-nonfiction": { "command": "npx", "args": ["etincel", "serve"] } } }

From a local clone instead: npm install && npm run build, then point args at ["/path/to/etincel/dist/server.js"] with "command": "node".

Remote (hosted, multi-tenant)

A hosted version is also available at etincel.ai, exposing the same tools over Streamable HTTP (https://etincel.ai/api/mcp) 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 yellow

Exits 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: orange

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 / allowedWords merge alongside whatever's in your account/style dictionary; register/threshold act as repo-wide defaults that an explicit --register/--threshold flag still overrides.
  • instructions is free text, folded into get_style_guide's instructions for *every* style, not just the team one, ahead of your own account-level global instructions: the team-wide equivalent of set_style_instructions with no styleId, but committed to the repo instead of living in one person's account.
  • style defines a shared "house voice" from dials, addressable everywhere as styleId: "team" (get_style_guide, and once forked into a real trained voice with fork_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_styles includes it automatically when a .etincelrc in 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/.

What's in here

  • An MCP server (src/server.ts) exposing twenty tools:
  • list_styles: premade tone presets,

只显示了开头部分;其余内容请在仓库中阅读