Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Deterministic ebook-to-markdown pipeline with MCP tools to browse, search, and read your books.
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LIB_HOMEYou need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"librarian": {
"command": "uvx",
"args": [
"librarian-cli"
],
"env": {
"LIB_HOME": "your-value"
}
}
}
}Run this in your terminal
claude mcp add librarian --env LIB_HOME=your-value -- uvx librarian-cliFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"librarian": {
"command": "uvx",
"args": [
"librarian-cli"
],
"env": {
"LIB_HOME": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"librarian": {
"type": "stdio",
"command": "uvx",
"args": [
"librarian-cli"
],
"env": {
"LIB_HOME": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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LIB_HOME envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
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This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 4 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Context7, Codebase Memory, Exa
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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
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.
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Turn any ebook into clean, token-counted Markdown chapters — let Claude read your bookshelf over MCP and catch it misquoting your books. Deterministic RAG: no embeddings, no network, no API keys.
Any input format — FB2, EPUB, DOCX, HTML, TXT/MD, text-layer PDF — becomes a directory of clean chapters with token counts. No network, no LLM, no randomness: the same input always produces byte-identical output.
uv tool install librarian-cli
Offline contract: install and runtime need no network (the tokenizer's vocabulary is vendored in the package).
lib ingest examples/*.epub
lib list lib find curiouser lib get --budget 3000
| Command | Purpose |
|---|---|
lib ingest [--force] [--no-keep-source] [--config cfg.toml] [--verbose] | Process books into the library; prints a file · id · status · score table. |
lib list [ ] | No argument — all books; with an id — that book's chapters (n, title, tokens, summary). |
lib get | Print chapters by range (1-3,7) to stdout. |
lib get --budget N [--from K] | Greedily print consecutive chapters from K while the token sum stays ≤ N. |
lib find [--limit 10] [--book ] [--reindex] [--json] | Full-text search across chapters and titles/authors library-wide (bm25, snippets, RU/EN stemming). |
lib info | JSON: book metadata + quality metrics. |
lib doctor [ ] | No id — books in review and broken directories; with id — that book's report. |
lib reingest --all [--config cfg.toml] [--verbose] | Rebuild the library from source/ with the current code/config. |
lib rm | Delete a book and rebuild the index. |
lib serve [--library ] | Stdio MCP server over the library. |
lib verify "quote" [--book ID] [--json] [--limit N] | Check a quote against one book or attribute it across the library. |
Library root: --library (or the LIB_HOME env var, default ./library). Data goes to stdout, diagnostics to stderr. Exit codes: 0 success, 1 runtime error, 2 usage error.
librarian-cli ships a built-in stdio MCP server with 6 read-only tools — list_books, list_chapters, find, get_chapters, book_info, verify_quote — so Claude can browse the catalog, search it, pull chapters under a token budget, and check its own quotes against the source on its own: deterministic RAG with no embeddings, no network, and no API keys.
Claude Code:
claude mcp add librarian --env LIB_HOME=$HOME/books -- uvx librarian-cli
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": { "librarian": { "command": "uvx", "args": ["librarian-cli"], "env": { "LIB_HOME": "/path/to/books" } } } }
*An MCP server that catches Claude misquoting your books.*
lib verify "quote" checks whether a quote actually appears in your library, verbatim — punctuation, case, ё/е, and markdown formatting don't count. Two modes:
--book ): full scan of one book — "does this book actually say this?" Works without the search index.--book): attribution across the whole library via FTS5 candidates — "which book is this from?" The quote needs at least 5 significant words (stop words don't count), or the check is skipped with verdict: null.lib verify "Рукописи не горят" --book bulgakov-master-i-margarita
lib verify "рукописи не горят никогда"
| verdict | meaning |
|---|---|
exact | matches after normalization (punctuation/case/ё/typography don't count) |
close | similarity ≥ 0.95 — near-exact, differences shown as a word-diff |
distorted | similarity ≥ 0.75 — the right place, but the quote is misremembered |
not_found | similarity < 0.75 — nothing like it in the book/library |
null | check wasn't run: empty quote, or a short quote without --book |
Exit codes (grep-style semantics, a deliberate departure from the project's usual "1 = runtime error" — see docs/MILESTONES.md deviation 38):
| exit | case | stdout |
|---|---|---|
| 0 | exact / close — quote confirmed | full report / JSON |
| 1 | distorted / not_found — not confirmed | full report / JSON |
| 1 | runtime error (unknown book id, no search index, locked index) | empty |
| 2 | usage error: empty/short quote (verdict: null), --limit < 1 | empty (message on stderr) |
Script discriminator: exit 1 with non-empty stdout means "checked, not confirmed"; exit 1 with empty stdout means an error (diagnostics went to stderr instead). Exit `0` includes `close` — a strict CI gate must check verdict == "exact" in the --json output, not the exit code alone.
Every book gets a score from five metrics (coverage, structure, garbage, encoding, dehyphenation): ok (score ≥ 0.90, no hard triggers) — saved silently; review (0.60 ≤ score < 0.90, or triggers present) — saved with a warning, details via lib doctor ; failed (score < 0.60) — not saved. Scans and password-protected PDFs honestly fail (OCR and DRM removal are out of scope).
The pipeline has no network access, no LLM calls, and no randomness — the same input file always produces byte-identical output. That makes ingestion reproducible and cacheable, and it's what makes lib serve's RAG deterministic: no embeddings to drift, no model calls to vary between runs.
review.lib verify: quotes spanning a chapter boundary are not supported (v1) — the best you'll get is distorted on one half.lib verify: close on a single-word replacement is realistic from ~150 characters of quote; shorter quotes with a replaced word honestly land in distorted — a third of a three-word quote really is a distortion.lib verify shelf mode (no --book) needs the FTS5 search index; book mode (--book ) works without it in the CLI. lib serve as a whole still requires FTS5 — it syncs the index at startup regardless of which tool gets called.lib verify in book mode scans the whole chapter text in pure Python; a long book can take a few seconds of CPU. The MCP tool runs it in a worker thread so it doesn't block the rest of the server.See README.ru.md for the Russian documentation.