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.

Related MCP server: CodeAlive MCP

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

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

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

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

Tools

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

• AO3 access approach builds on ao3_api by wendytg.

• All fanworks belong to their authors on the Archive of Our Own, a project of the Organization for Transformative Works.

License

MIT