Command Palette

Search for a command to run...

UnylyUnyly
Browse all

Pydantic Zotero

FreeNot checked

An MCP server that gives AI agents read access to a Zotero library, enabling search, item metadata, collections, tags, notes, and full-text search of attached P

GitHubEmbed

About

An MCP server that gives AI agents read access to a Zotero library, enabling search, item metadata, collections, tags, notes, and full-text search of attached PDFs.

README

An MCP server that gives AI agents read access to a Zotero library — search, item metadata, collections, tags, the researcher's own notes, and the indexed full text of attached PDFs.

See PRD.md for requirements.

Status: M1 (read core) + M2 (full text) implemented. Citation formatting and export (M3), prompts (M4), and write tools (M5) are not built yet — see Not yet implemented.

Install

As a tool (pipx)

Installs the zotero-mcp command into its own isolated environment:

pipx install pydantic-zotero-mcp        # or: pipx install /path/to/checkout
zotero-mcp --help

Into another project's environment

uv add pydantic-zotero-mcp              # or: uv pip install pydantic-zotero-mcp

For development on this server

git clone https://github.com/jmlon/pydantic-zotero-mcp
cd pydantic-zotero-mcp
uv sync           # creates ./.venv from this project's own lock file
uv run pytest
uv run ruff check

Configure

Get a read-only API key and your numeric user ID from https://www.zotero.org/settings/keys. The library ID is the number, not your username.

export ZOTERO_API_KEY=...
export ZOTERO_LIBRARY_ID=123456      # numeric
export ZOTERO_LIBRARY_TYPE=user      # or group
Variable Default Purpose
ZOTERO_API_KEY Web API key (required unless ZOTERO_LOCAL=true)
ZOTERO_LIBRARY_ID Numeric user or group ID
ZOTERO_LIBRARY_TYPE user user or group
ZOTERO_LOCAL false Read the Zotero 7 desktop API instead: no key, no rate limit, read-only
ZOTERO_ALLOW_WRITES false Reserved for M5; no write tools exist yet
ZOTERO_FULLTEXT_MAX_CHARS 100000 Default full-text ceiling; per-call max_chars overrides it
ZOTERO_DEFAULT_STYLE chicago-note-bibliography Reserved for M3
ZOTERO_MAX_CONCURRENCY 4 Upstream request cap (Zotero asks for ≤ 4)
ZOTERO_MCP_TRANSPORT stdio stdio or http
ZOTERO_MCP_HOST 127.0.0.1 HTTP bind address
ZOTERO_MCP_PORT 8000 HTTP port
ZOTERO_MCP_PATH /mcp HTTP mount path
ZOTERO_MCP_AUTH_TOKEN Bearer token; required for HTTP

CLI flags override environment variables.

Run

Once installed, zotero-mcp is the entry point — no interpreter path, no python -m, no working directory to get right, which is what an MCP client's command: wants:

# stdio (default) — an agent launches this as a subprocess
zotero-mcp

# streamable HTTP — requires ZOTERO_MCP_AUTH_TOKEN
ZOTERO_MCP_AUTH_TOKEN=secret zotero-mcp --transport http --port 8000

# read the Zotero desktop app instead of the web API
zotero-mcp --local

From a checkout, without installing, python -m zotero_mcp still works:

uv run python -m zotero_mcp

Starting with --transport http and no token exits 2 rather than serving unauthenticated: this is a read channel into a personal library.

In-memory (embedded in an agent process)

No subprocess, no socket. Settings are injected, so the host never needs environment variables:

from fastmcp import Client
from zotero_mcp import ZoteroSettings, create_server

server = create_server(
    ZoteroSettings(
        api_key=key,
        library_id="123456",
        library_type="user",
    )
)

async with Client(server) as client:  # lifespan opens here
    result = await client.call_tool("search_items", {"query": "attention"})
    print(result.structured_content["items"])  # dict; result.data is a model

Importing zotero_mcp has no side effects — no config read, no client built, no network — which is what makes embedding possible. There is a test that enforces it.

Discovery via entry point

For host applications that discover bundled MCP servers through Python entry points, this package declares one in the deep_research.mcp_servers group:

[project.entry-points."deep_research.mcp_servers"]
zotero = "zotero_mcp:build_server"

build_server() takes no arguments and derives settings from the environment — install this package into the host's environment and the host can resolve and run the server in-process by the name zotero, without importing anything by path from a config file.

One tuning note for automated hosts: this server's default full-text ceiling is 100,000 characters (~25–30k tokens for a single get_item_fulltext call), which is generous for interactive use and far too large for an agent making many calls against a token budget — pass a smaller max_chars per call, or lower ZOTERO_FULLTEXT_MAX_CHARS.

Tools

Tool Purpose
get_library_info Size, mode, permissions. Cheap orientation call — use it first
search_items Primary entry point. mode="metadata" or "fulltext" (searches PDF text)
list_recent_items Recently added items, newest first
find_item_by_identifier "Do I already have this?" by DOI, ISBN, arXiv ID, or key
get_item Full metadata; include_children=True also lists attachments and notes
get_item_children Attachments and notes, with may_have_fulltext per attachment
get_item_notes The researcher's own notes, HTML stripped
get_item_fulltext Indexed attachment text; resolves parent → attachment
list_collections Nested collection tree
list_collection_items Items in one collection
list_tags Tag vocabulary, optionally prefix-filtered

Resources: zotero://library/info, zotero://collections, zotero://items/{key}, zotero://items/{key}/fulltext, zotero://collections/{key}/items, zotero://schema/item-types, zotero://schema/item-types/{type}/fields.

Design notes

Projection is the point. Raw Zotero JSON is ~1 KB per item of links, library, meta, and empty type fields. zotero_mcp/projection.py reduces a 25-item page from ~6,100 to ~2,400 estimated tokens (39% of raw), under the PRD's 4,000 budget. Null fields are dropped at serialization by CompactModel.

pyzotero is synchronous and stateful. Zotero.request and Zotero.links are overwritten by each call, and Total-Results is read back off the instance afterwards — so one shared client used concurrently would report another call's totals. gateway.py keeps a pool of up to ZOTERO_MAX_CONCURRENCY clients, checks one out per operation, and reads response metadata inside the same worker thread that holds it. Every call goes through anyio.to_thread.run_sync so the event loop never blocks.

Backoff is pyzotero's job. pyzotero ≥ 1.13 already honours Backoff / Retry-After and retries 429 internally, so the gateway does not reimplement it. It adds a bounded 3-attempt retry for transient transport and 5xx failures only.

Nothing is silently truncated. Searches report total_matched, truncated, and next_start; full text reports total_chars and truncated.

Results are candidates, not verdicts (PRD D3). find_item_by_identifier returns matched_on (key / doi / title / identifier / none) plus a confidence and all plausible candidates — a pre-print and its published version both survive. The caller filters.

Deviations from the PRD

Worth knowing about, since each was a judgment call made during implementation:

  1. No module-level mcp object. PRD 7.2 asked for both a module-level mcp = create_server() and no import-time side effects. Those conflict: building the server validates config, so a module-level instance raises ImportError on any machine without Zotero env vars, and breaks the in-memory path it was meant to support. Only create_server() / build_default_server() exist.

  2. Write tools will be registered conditionally, not enabled=False. PRD 5.5 specified @mcp.tool(enabled=False), but FastMCP 3.x has no enabled kwarg, and a disabled-but-listed tool still costs context. When M5 lands, write tools will simply not be registered unless ZOTERO_ALLOW_WRITES=true.

    This server targets FastMCP 3.x. Two 3.x specifics shape the code here: enabled is gone from the decorators, and result.data is a generated pydantic model while result.structured_content is the plain dict — the tests assert on the latter, which also verifies null-omission on the wire.

  3. has_fulltext is three-valued. PRD 6 typed it bool, but determining it for a parent item requires a separate children request per item, which would make a 25-item search 26 requests. It is False when an item has no children at all, True/False for attachments and after get_item(include_children=True), and null (omitted) when undetermined. ItemSummary.num_children gives the cheap signal.

  4. find_item_by_identifier returns CitationMatch, not ItemSummary | None. Follows from D3 — the old signature made exactly the identity call that decision moved to the client.

  5. matched_on gained key and identifier beyond the PRD's four values, to distinguish an exact key hit from a weak search hit.

  6. list_recent_items(since_days=...) filters locally. Zotero has no server-side date filter, so a narrow window can return fewer items than limit; the response hint says when that happened.

Tests

uv run pytest      # 80 passed

The suite uses FastMCP's in-memory transport against a FakeZotero that reproduces pyzotero's read-metadata-off-the-instance behaviour. No network, no subprocess, no real credentials. Coverage: schema surface, projection and token budget, pagination and truncation reporting, full-text ceiling and parent resolution, match recall (pre-print/published pairs both returned), error message quality, resource template validation including traversal attempts, config validation, CLI precedence, gateway retry/caching, and an import-purity check that fails if importing the package touches the network.

Not yet implemented

  • M3format_citation, format_bibliography, export_items
  • M4 — the four prompts (literature_review, find_related_work, check_citations, summarize_reading), Logfire instrumentation
  • M5 — write tools (create_item, update_item_fields, add_item_tags, add_items_to_collection, create_note) with version-checked PATCH semantics. Deletion is out of scope permanently.

from github.com/jmlon/pydantic-zotero-mcp

Install Pydantic Zotero in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install pydantic-zotero-mcp

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add pydantic-zotero-mcp -- uvx pydantic-zotero-mcp

Step-by-step: how to install Pydantic Zotero

FAQ

Is Pydantic Zotero MCP free?

Yes, Pydantic Zotero MCP is free — one-click install via Unyly at no cost.

Does Pydantic Zotero need an API key?

No, Pydantic Zotero runs without API keys or environment variables.

Is Pydantic Zotero hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Pydantic Zotero in Claude Desktop, Claude Code or Cursor?

Open Pydantic Zotero on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

Related MCPs

Compare Pydantic Zotero with

Not sure what to pick?

Find your stack in 60 seconds

Author?

Embed badge for your README

Browse similar

All ai MCPs