Context7
Up-to-date docs for AI agents
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
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。
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。
选择你使用的 AI 应用,然后复制设置。
GEMINI_API_KEY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
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。
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。
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。
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。
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
注册名称已通过 GitHub 账户 ArturLys 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
你需要填写:GEMINI_API_KEY
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)。
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。
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)。
同一分类中有:Context7, Codebase Memory, Exa
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
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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。
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
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.
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.
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
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.
| Param | Env var | Default | What it does |
|---|---|---|---|
--api-key | GEMINI_API_KEY | — | Gemini API key (required). |
--model | GEMINI_MODEL | gemini-flash-latest | Model the reader uses. |
--backup-model | GEMINI_MODEL_BACKUP | gemini-flash-lite-latest | Fallback model when the main one is throttled. |
--min-interval | AO3_MIN_INTERVAL | 0.6 | Minimum seconds between AO3 requests. |
| Tool | What it does |
|---|---|
search_works | Search 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_tags | Live autocomplete — fuzzy wording → canonical AO3 tag, fandom, ship, or character names. |
get_work | Full metadata card for one work: tags, stats, summary, series info. |
read_works | Reads 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.
--min-interval) and honoring Retry-After. AO3 is volunteer-run; the politeness is deliberate.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.rating filter and AO3's warning tags to control what gets fetched.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
MIT