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Overview

Metabook is a Book Structure API: give it a title, an ISBN, a Gutenberg ID, or an EPUB file, and it returns the book's structural schema — what kind of book it is and how it's shaped — without ever returning the text itself.

Under the hood it locates the book via Gutendex (or walks your uploaded EPUB's spine), downloads and cleans the text, detects the structural schema, and counts everything at every level.

title / ISBN / Gutenberg ID ──► Gutendex ──► fetch + clean ──┐
                                                             ├──► detect schema ──► counts-only JSON
your .epub ──► Vercel Blob ──► package doc + spine XHTML ────┘

✨ Features

• 🔍 Fuzzy search — find books by title or author via Gutendex, or go straight to an ISBN / Gutenberg ID
• 🧬 Schema detection — classifies each book as scripture, sectioned_book, standard_book, essay_collection, or flat, with a confidence rating
• 🔢 Counts, not content — chapters, paragraphs, sentences, clauses, and words per node; a word node is just its index. No book text is ever included in a response
• 📤 Bring your own EPUB — POST /api/books/upload stores the file in Vercel Blob and analyses it with the same pipeline
• 🔌 Two interfaces, one service layer — a FastAPI REST API and a FastMCP server share the same core
• 🖥️ Native desktop client — a GPUI example app with an animated structure tree and a synced JSON code editor

Detail levels

The detail parameter controls how deep the returned tree nests beneath each paragraph:

detail	Nested nodes
paragraph	paragraphs only (counts for the rest)
sentence	+ sentence nodes
clause	+ clause nodes
word	+ word nodes (index + position only)

Token counts

Pass an optional tokenizer query parameter naming a Hugging Face tokenizer repository (e.g. bert-base-uncased) and every node in the tree carries a token count alongside its word count — special tokens excluded, so parent totals equal the sum of their children. The response metadata echoes the resolved tokenizer name and its vocabulary size. The tokenizer is fetched lazily on first use (cached on disk and in memory afterwards); an unknown name returns 422, a transient fetch failure on cold start returns 503. When the parameter is omitted, no token counts are computed and the response is unchanged.

curl "http://127.0.0.1:8000/api/books/structure?title=Pride+and+Prejudice&tokenizer=bert-base-uncased"

🚀 Quick start

make setup              # install dependencies (uv sync)
make dev                # run the API with auto-reload on :8000
make test               # run the test suite
make docker-up          # or run it via docker compose

Then open the interactive docs at http://127.0.0.1:8000/api/docs, or try:

curl "http://127.0.0.1:8000/api/books/structure?title=Pride+and+Prejudice&detail=sentence"

EPUB uploads

Uploads need a Vercel Blob read-write token in the environment (or .env / .env.local):

export BLOB_READ_WRITE_TOKEN=vercel_blob_rw_...

If the project is linked to Vercel, vercel env pull writes the token to .env.local (gitignored), which the app loads automatically — values there override .env.

Uploads collection (MongoDB, optional)

Every book a user uploads or selects from search results is persisted as a document in a MongoDB uploads collection: the book metadata, format (epub), the Vercel Blob link, and the scan state (scanned yet, last scanned, scope, schema, total token count). The structure tree itself is never stored. Set MONGODB_URI to enable (empty = disabled, no behavior change); re-selecting the same Gutenberg book updates its document instead of duplicating it:

export MONGODB_URI=mongodb://localhost:27017

Browse what's stored via GET /api/books/uploads.

🌐 REST API

Method	Endpoint	Purpose
GET	/api/books/structure	Analyse by title, isbn, or gutenberg_id (+ detail, tokenizer)
GET	/api/books/structure/schemas	List the supported structural schemas
POST	/api/books/upload	Upload an EPUB and analyse it
GET	/api/books/uploads	List persisted upload documents (needs MONGODB_URI)
GET	/health	Liveness + cache stats

Interactive OpenAPI docs live at /api/docs.

🤖 MCP server

A FastMCP server is mounted at /mcp, so agents can use the same service layer through three tools:

Tool	Description
search_book_structure	Analyse a book by title, ISBN, or Gutenberg ID
upload_book_epub	Analyse an EPUB passed as base64 or a URL
list_supported_schemas	Enumerate the structural schemas

🖥️ Desktop example (GPUI)

example/ is a native macOS client built with GPUI and gpui-component: a sidebar workspace whose Dashboard holds fuzzy search, EPUB drag-and-drop, and a cover grid of every book the API has scanned; selecting a book gives an animated lazily-materialised structure tree beside a read-only JSON code editor (tree-sitter highlighting, folding) that scrolls to and highlights whichever node you select. Light and dark themes, spring animations, collapsible sidebar.

More screenshots

Search results	Dark mode

Run it (API first, then the app):

make dev

cd example && cargo run

Or run both with one command (Ctrl-C stops both):

make serve

See example/README.md for the Metabook.app bundle (with app icon) and METABOOK_API configuration.

🌳 Branching and release

CI/release pipeline scaffolded from exegia/corpora-py: same branch model, GitHub Actions workflows, composite actions, and make-driven release automation.

See .github/WORKFLOW.md for the full branch model, versioning rules, and workflow reference. Quick summary:

<type>/<slug> --PR--> dev --(daily/manual)--> next --cut--> release/vX.Y.Z --draft PR--> main
                 (deleted on merge)         (preview)                       (deleted on release)

Common commands

make help                # list all targets
make ci                  # everything CI runs on a PR (lint + test)
make pack                # build the publishable wheel
make rulesets-diff       # rulesets GitHub currently has
make rulesets-apply      # push .github/rulesets/*.json

Bootstrap

There are no dev / next branches until the first wrapup. Run the Release workflow manually (Actions → Release → Run workflow), or locally:

make bootstrap-lanes

📄 License

MIT © Emmanuel De Freitas