Alexandria

A local, single-user knowledge store with an MCP interface. Ingests PDFs, HTML, plain text and markdown from folders or URLs; deduplicates by content hash; retrieves with hybrid keyword + semantic search. Everything lives in one portable SQLite file — no external services, no cloud.

It's designed to be driven by an LLM agent as readily as by a person: the same tool surface is exposed over MCP (stdio for local clients, Streamable HTTP for remote ones) and a browser UI, all against one corpus.

Highlights

Hybrid retrieval — BM25 (SQLite FTS5) fused with vector search (sqlite-vec) via reciprocal rank fusion.
Content-addressed dedup — three cheap layers collapse the same document across renamed files, re-downloads, and format conversions.
Mixed corpora — research papers and household bills coexist in one index; categories and tags keep them from crowding each other out.
Zero-shot labelling — user-authored category/tag "anchors" let a classifier suggest metadata for new documents, with no training step.
Agent-native — 19 MCP tools spanning ingest, search, curation, and metadata, identical across the stdio and HTTP transports.
Portable — one SQLite DB (metadata + FTS + vectors) plus a content-addressed blob store; back it up by copying a directory.

See SPEC.md for the full design document.

How it works

Alexandria is one Python package — ingestion, retrieval, and a catalog — behind a shared tool surface. That surface is reachable three ways, all co-hosted on one process and one SQLite file: an MCP stdio server, an MCP Streamable-HTTP server, and a Starlette web UI.

  MCP stdio ─┐
  MCP HTTP  ─┼─▶  ingest · search · catalog  ─▶  SQLite (FTS5 + sqlite-vec) + blobs/
  Web UI    ─┘

Ingestion turns each file or URL into deduplicated, searchable text:

fetch → sniff type → hash raw bytes → extract → normalize → hash text → chunk → embed → index

Extraction is per-type (pypdf for PDFs, trafilatura for HTML, UTF-8 for text/markdown); normalization applies NFKC folding, ligature expansion, and hyphenated-line-break repair — the biggest searchability win for LaTeX-generated PDFs. Deduplication runs three layers in order — same source, same raw-byte hash, same normalized-text hash — so re-downloads, renamed copies, and PDF↔HTML re-exports of the same content collapse to a single document.

Retrieval runs two searches per query and fuses them: BM25 over FTS5 and cosine nearest-neighbours over sqlite-vec, combined with reciprocal rank fusion (no score calibration needed), then filtered by category and tags.

Storage is a single portable directory: one SQLite database holding metadata, full text, the keyword index, and the vector index, plus a content-addressed blobs/ tree of the original bytes for provenance and re-extraction.

Install

Requires Python 3.12+ and uv.

uv sync

The first ingest downloads the embedding model (BAAI/bge-small-en-v1.5, ~130 MB) into your HuggingFace cache.

Data directory

Alexandria stores everything under $XDG_DATA_HOME/alexandria/ (falling back to ~/.local/share/alexandria/). Override with ALEXANDRIA_HOME.

$ALEXANDRIA_HOME/
├── alexandria.db     # SQLite with FTS5 + sqlite-vec
├── blobs/            # original bytes, content-addressed by sha256
└── config.toml       # (optional) user overrides

CLI

# ingest a single file with a category and tags
uv run alexandria ingest ~/Docs/paper.pdf --category research --tags ml,retrieval

# walk a folder (recursive, supported extensions only by default)
uv run alexandria ingest-folder ~/Docs/Bills --category bills --tags 2026

# fetch and ingest a URL; category may come from config.toml rules
uv run alexandria ingest-url https://arxiv.org/abs/2004.04906

# search (hybrid RRF fusion by default)
uv run alexandria search "reciprocal rank fusion" --limit 5
uv run alexandria search "8891-3320-2" --category bills --mode fts
uv run alexandria search "how do dense retrievers work" --mode vec

# browse the corpus
uv run alexandria list --category research
uv run alexandria info

Config (optional)

$ALEXANDRIA_HOME/config.toml — everything has sensible defaults; you only need to override what you care about.

[embeddings]
model = "BAAI/bge-small-en-v1.5"
device = "cpu"                   # "cpu" | "cuda" | "mps"

[chunking]
tokens = 800
overlap = 100

[storage]
keep_blobs = true                # keep original bytes for provenance

[extractors.pdf]
backend = "pypdf"                # "pypdf" | "marker"
device  = "auto"                 # "auto" | "cuda" | "cpu" | "mps"

[http]
user_agent = "Alexandria/0.1"
respect_robots_txt = true
max_redirects = 5
timeout_seconds = 30

# URL heuristics: applied to ingest-url when the caller doesn't supply a category.
# host_glob uses fnmatch (so *.example.com matches subdomains).
[[category_rules]]
host_glob = "arxiv.org"
category  = "research"
tags      = ["paper"]

[[category_rules]]
host_glob = "*.pge.com"
category  = "bills"
tags      = ["utility", "electric"]

MCP integration

Alexandria exposes its full surface over MCP — 19 tools spanning ingestion (ingest_folder_tool, ingest_url_tool), retrieval (search_tool, get_document_tool, list_documents_tool, get_catalog_tool, get_original_tool), curation (delete_document_tool, rename_category_tool, delete_category_tool, rename_tag_tool, delete_tag_tool), metadata suggestions (suggest_metadata_tool, suggest_metadata_bulk_tool), and label anchors (list_anchors_tool, set_anchor_tool, delete_anchor_tool, import_anchors_tool, export_anchors_tool). The tool surface is identical across both transports.

Local (stdio)

For clients on the same machine (Claude Code on your laptop hitting a local corpus). Add to your MCP client (e.g. ~/.claude/mcp.json):

{
  "mcpServers": {
    "alexandria": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/Alexandria", "alexandria", "mcp"]
    }
  }
}

Remote (Streamable HTTP)

For agents on other machines hitting a central corpus (typically the GPU host running marker). On the server:

# generate a token once
openssl rand -hex 32 > $ALEXANDRIA_HOME/auth_token && chmod 600 $ALEXANDRIA_HOME/auth_token

# start the server, exposed on the LAN
uv run alexandria mcp-http --host 0.0.0.0 --port 8765 \
    --auth-token-file $ALEXANDRIA_HOME/auth_token

Token resolution order: ALEXANDRIA_AUTH_TOKEN env var > --auth-token-file flag > [network] auth_token_file in config.toml. Missing token when binding a non-loopback host aborts startup — pass --no-auth for trusted-network deploys (Tailscale, WireGuard, LAN behind a firewall).

On the client:

{
  "mcpServers": {
    "alexandria-remote": {
      "url": "https://alexandria.example.com/mcp",
      "headers": {
        "Authorization": "Bearer <paste-token>"
      }
    }
  }
}

TLS is out of scope for the app — terminate at a reverse proxy. Sample Caddy config:

alexandria.example.com {
    reverse_proxy 127.0.0.1:8765
}

Or expose only inside a mesh network (Tailscale/WireGuard) and skip TLS altogether — --no-auth is reasonable there since the mesh already gates access.

Web UI

Alexandria ships with a browser UI that co-hosts on the same ASGI app as mcp-http — one port, one systemd unit, one auth strategy split between two credentials (the MCP bearer token stays; the web password is separate).

Enable

The web UI is on by default whenever alexandria mcp-http runs. Set a password before first browser access:

alexandria set-web-password        # prompts twice; writes chmod-600 bcrypt hash

Then visit http://<host>:8765/ and log in. Nothing further is needed on the MCP client side — the MCP bearer token and the web password are independent.

What's there

/ — landing: catalog totals, drop zone for multi-file upload (PDF / HTML / TXT / MD), live activity feed of ingest jobs.
/search — hybrid FTS + vector search, filterable by category and tags. Hit cards link into the doc detail page. FTS matches are highlighted with <mark> in the UI and **…** in the JSON/MCP API.
/documents — filterable, paginated document browser.
/documents/{id} — full metadata, sources, tags, and a lazy-loaded "Show extracted text" panel.

Config

[web]
enabled = true          # set to false to disable page routes entirely
title = "Alexandria"    # shown in header + page title
max_upload_mb = 100     # per-file cap; larger uploads get 413
password_hash_file = ""   # default: $ALEXANDRIA_HOME/web_password_hash
session_secret_file = ""  # default: $ALEXANDRIA_HOME/session_secret (auto-generated)
session_max_age_days = 30

API surface (browser-side, not MCP)

/api/* accepts EITHER the MCP bearer token (for curl scripting) OR a valid alx_session cookie (for the browser). Endpoints:

GET    /api/info                     server + model info
GET    /api/catalog                  totals + facets
GET    /api/search?q=…               same shape as MCP search_tool
GET    /api/documents                filterable, paged
GET    /api/documents/{id}           optional ?include_text=true
POST   /api/upload                   multipart files[] + category + tags
POST   /api/ingest-url               {url, category, tags}
GET    /api/jobs                     recent job rows
GET    /api/jobs/{id}
POST   /api/jobs/{id}/cancel
GET    /api/jobs/stream              SSE stream of status transitions

Ingest via /api/upload and /api/ingest-url is asynchronous: each file/URL becomes a jobs row, processed by a single background worker. If the server restarts mid-job, that row is swept to error; queued rows resume.

Curate

Doc detail (/documents/{id}) has an Edit button (rewrite category + tags, with a datalist of existing categories) and a Delete button (native browser confirm, cascade to chunks + FTS + vec + blob, redirect to /documents).
/taxonomy lists categories and tags with counts. Rename or delete inline; rename into an existing target merges. Confirmation prompts warn about affected doc counts.
All destructive operations are permanent — no undo.

Same actions are available via MCP for agent-driven curation:

delete_document_tool(doc_id)              → {"deleted": true|false}
rename_category_tool(old, new)            → {"affected": N}
delete_category_tool(name)                → {"affected": N}
rename_tag_tool(old, new)                 → {"affected": N}
delete_tag_tool(name)                     → {"affected": N}

Deploy notes

--no-auth bypasses both the bearer check and the web password gate, for trusted-network deploys (Tailscale, WireGuard, LAN). The safety rail still refuses non-loopback binds without either an auth token or --no-auth.
The web UI expects same-port coexistence with /mcp. If you're reverse- proxying, path both /mcp and / to the same upstream.

Development

uv sync                           # dev deps included in `dev` group
uv run pytest                     # 263 passing (+1 GPU-gated), ~20 s
uv run ruff check src tests

Tests use hash-based fake embeddings by default (see tests/conftest.py::fake_embed) so ingest/dedup/catalog tests run fast. Search tests use the real embedding model via sentence-transformers' local cache.

PDF backends

Two extractors, selected per install via [extractors.pdf] backend:

pypdf (default) — no extra deps, fast on CPU, but math/tables come out as flattened plain text (fractions split across lines, sub/superscripts lost). No OCR: scanned PDFs raise a "no extractable text" error.
marker — Torch-based, GPU-accelerated. Outputs markdown with $…$ and $$…$$ LaTeX for math, #-headings for structure, and OCR (surya) on scanned pages. Downloads ~2GB of weights to ~/.cache/datalab/ on first run. CPU inference is impractical (tens of minutes per paper); a modest GPU (~8GB VRAM) is enough.

Install marker only where you'll run it (server-primary is the intended shape):

uv sync --extra marker            # torch + marker-pdf + surya

then in $ALEXANDRIA_HOME/config.toml:

[extractors.pdf]
backend = "marker"
device  = "auto"                 # picks cuda > mps > cpu

If marker raises during ingest, Alexandria logs a warning and falls back to pypdf on that document so ingest stays robust.

Deduplication

Three cheap layers, always run, in this order:

Source — same (source_kind, source_uri) was ingested before.
Raw bytes — sha256(bytes) matches an existing document.
Normalized text — sha256(normalized_text) matches (catches re-exported PDFs, mirrored HTML, format conversions).

A duplicate hit updates last_seen_at, records the alternate source_uri, and merges any new tags. Near-duplicate detection (MinHash/simhash) is not implemented.

Label anchors

Categories and tags can be set by hand at ingest, but Alexandria can also suggest them — with no training step. Instead of a trained classifier, you write a short prose description of what each label means (an anchor), and the same embedding model that powers search embeds it. A new document's chunks are compared against those anchor embeddings and against the labels of its nearest already- labelled neighbours; anything clearing a similarity threshold is offered as a suggestion. Nothing is auto-applied — the home page and suggest_metadata_tool surface suggestions for one-click confirmation, and duplicates or labels the user gave at ingest are skipped.

Because an anchor is just a sentence, adding or reshaping a label is a text edit, not a retrain. anchors.starter.json ships a starter taxonomy (10 categories, 21 tags) to import and iterate on — from the /anchors page or the MCP anchor tools (list_anchors_tool, set_anchor_tool, import_anchors_tool, export_anchors_tool). Matching thresholds live under [classify] in config.toml, with separate similarity floors for categories and tags: every document needs a category, so its bar is lower, while tags are optional and held to a stricter one.

License

MIT — see LICENSE.

Name		Name	Last commit message	Last commit date
clients/claude-desktop		clients/claude-desktop
docs/screenshots		docs/screenshots
src/alexandria		src/alexandria
tests		tests
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
SPEC.md		SPEC.md
anchors.starter.json		anchors.starter.json
pyproject.toml		pyproject.toml
uv.lock		uv.lock

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Alexandria

How it works

Install

Data directory

CLI

Config (optional)

MCP integration

Local (stdio)

Remote (Streamable HTTP)

Web UI

Enable

What's there

Config

API surface (browser-side, not MCP)

Curate

Deploy notes

Development

PDF backends

Deduplication

Label anchors

License

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Alexandria

How it works

Install

Data directory

CLI

Config (optional)

MCP integration

Local (stdio)

Remote (Streamable HTTP)

Web UI

Enable

What's there

Config

API surface (browser-side, not MCP)

Curate

Deploy notes

Development

PDF backends

Deduplication

Label anchors

License

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