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Search AO3 and have fics read by a secondary model before they're recommended
Search AO3 and have fics read by a secondary model before they're recommended
A well-intentioned fanfiction discovery server with reasonable code quality and appropriate permissions for its purpose. Primary concerns are incomplete input validation on user-controlled search parameters, potential for overly broad or malformed queries reaching AO3, and Gemini API key exposure via command-line arguments. The server's core functionality (scraping, caching, delegated reading) is sound, but some edge cases in query handling and error reporting could be hardened. Supply chain analysis found 6 known vulnerabilities in dependencies (0 critical, 6 high severity). Package verification found 1 issue.
6 files analyzed · 14 issues found
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This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: GEMINI_API_KEY
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-arturlys-ao3-mcp": {
"env": {
"GEMINI_API_KEY": "your-gemini-api-key-here"
},
"args": [
"ao3-mcp"
],
"command": "uvx"
}
}
}From the project's GitHub README.
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.
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 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.
| 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
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