原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Ao3 MCP

作者:ArturLys版本 0.1.2i★ –i在你的电脑上运行
注册名称io.github.ArturLys/ao3-mcp

安装

概览

作者提供的说明(英文原文)

Search AO3 and have fics read by a secondary model before they're recommended

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆
  • 你需要填写:GEMINI_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "ao3": {
      "command": "uvx",
      "args": [
        "ao3-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add ao3 --env GEMINI_API_KEY=your-value -- uvx ao3-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "ao3": {
      "command": "uvx",
      "args": [
        "ao3-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "ao3": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "ao3-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • GEMINI_API_KEY 机密 必填 env
    Gemini API key (free from https://aistudio.google.com/api-keys)

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。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

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7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 ArturLys 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7275 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7275 个服务器的 25% 更新
  • 基础检查结果等于或优于此分类中其他 7275 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

Ao3 MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 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?

你需要填写:GEMINI_API_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.2)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。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

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:★ 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

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
安装

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。

ao3-mcp

An MCP (Model Context Protocol) server that connects AI agents — Claude, Cursor, or any MCP client — to the Archive of Our Own. Search AO3 fanfiction with full filters, resolve fuzzy wording to canonical tags, and get fics *actually read* before they're recommended.

The trick: your agent never reads fic text. It delegates reading to a cheap secondary model (Gemini), which digests whole fics — even 150k-word novels — and returns structured reports. Your agent's context stays clean; the recommendations are based on the real text, not the blurb.

agent ──MCP──> server.py

├─ ao3.py AO3 scraping (no public API exists) — throttled and polite └─ reader.py Gemini reads the fics, reports back: plot, style, prose samples, content notes, a ranking

Why this beats blurb-based recommendations

An AO3 blurb is an ad written by the author. This server's workflow is: search wide (40–60 results), have the reader model read the shortlist — up to 20 full fics in one call — and recommend only what was actually read, with verbatim prose samples so quality is judged from the text itself.

Not just for finding your next read

If you write with an AI — fanfic, original fiction, roleplay — this doubles as an inspiration engine. Mid-scene, your agent can pull up how real fic authors handle the exact beat you're on:

Find three highly-kudosed fics where rivals are forced to share a bed, read them,

and tell me how each one builds the tension — pacing, POV, what they leave unsaid.

The reader reports back with structure, style notes, and verbatim prose samples, so the model gets grounded in how the trope is actually written — not what it imagines fanfic sounds like. Works the same for roleplay: pull reports on fics that nail a character's voice and feed them in as style reference.

Install

Requires Python 3.10+ and a free Gemini API key:

Go to aistudio.google.com/api-keys, sign in with any Google account, and click "Create API key". The free tier is enough — no billing setup needed.

pip install ao3-mcp

Add to your agent

Point command at ao3-mcp and pass your key with --api-key:

{

"mcpServers": { "ao3": { "command": "ao3-mcp", "args": ["--api-key", "YOUR_GEMINI_KEY"] } } }

Prefer to keep the key out of the args list? Drop --api-key and pass it in an env block instead — the server reads GEMINI_API_KEY from the environment as a fallback:

"env": { "GEMINI_API_KEY": "YOUR_GEMINI_KEY" }

Claude Code

claude mcp add ao3 -- ao3-mcp --api-key YOUR_GEMINI_KEY

Cursor

Cursor Settings → MCP → New MCP Server, paste the JSON config above.

Google Antigravity

Add the JSON config above to .gemini/antigravity/mcp_config.json.

VS Code / Copilot

code --add-mcp '{"name":"ao3","command":"ao3-mcp","args":["--api-key","YOUR_GEMINI_KEY"]}'

Then just ask:

Find me a completed enemies-to-lovers longfic in <fandom>, read the top candidates, and tell me which is best written.
Launch params
ParamEnv varDefaultWhat it does
--api-keyGEMINI_API_KEY—Gemini API key (required).
--modelGEMINI_MODELgemini-flash-latestModel the reader uses.
--backup-modelGEMINI_MODEL_BACKUPgemini-flash-lite-latestFallback model when the main one is throttled.
--min-intervalAO3_MIN_INTERVAL0.6Minimum seconds between AO3 requests.

Tools

ToolWhat it does
search_worksSearch AO3: fandom, ship, character, tags, rating, word count, completion, sorting. 20 results/page, up to 5 pages per call. The query field supports AO3's full search-operator syntax (words>10000, kudos>500, sort:kudos, …).
find_tagsLive autocomplete — fuzzy wording → canonical AO3 tag, fandom, ship, or character names.
get_workFull metadata card for one work: tags, stats, summary, series info.
read_worksReads 1–20 full fics with the secondary model and returns a structured report per fic — plot, characters, style, verbatim prose samples, content notes — plus a comparison ranking them against your question.

Fic downloads are cached locally for 24h, so re-reading a fic with a new question costs no AO3 requests.

Good to know

  • AO3 has no API — this scrapes its (clean) HTML, one request at a time, throttled to one every 0.6s by default (tune with --min-interval) and honoring Retry-After. AO3 is volunteer-run; the politeness is deliberate.
  • Cloudflare: AO3 blocks plain HTTP clients. This uses curl_cffi with a mobile-Safari TLS fingerprint, which passes as of writing. If requests start failing with 403 + cf-mitigated: challenge, change IMPERSONATE in ao3.py.
  • Privacy: fic text goes to Google's Gemini API for reading; nothing else leaves your machine, no telemetry.
  • Adult content: AO3 hosts works across all ratings. The server passes through whatever your search scopes — use the rating filter and AO3's warning tags to control what gets fetched.

Make it yours

It's a small, single-purpose server — a few hundred readable lines with no framework magic. Fork it and edit anything: rewrite the reader's prompt, swap in a different model, change the throttle, add a tool. That's the intended way to use it.

Run it from source:

git clone https://github.com/ArturLys/ao3-mcp.git

cd ao3-mcp python -m venv .venv source .venv/bin/activate # Windows: .venv\Scripts\activate pip install -r requirements.txt

python smoke_test.py YOUR_GEMINI_KEY # end-to-end check: search → download → digest python server.py --api-key YOUR_GEMINI_KEY # or point your client's command at this

Credits

License

MIT

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