Give AI agents instant, private access to your personal knowledge base. First source: Zotero.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
One-click editor setup isnβt available for this listing yet β we donβt have a confirmed install command, and weβd rather show nothing than point your editor at the wrong package or host. Follow the projectβs own setup instructions, linked above.
DocsAgent gives AI agents instant, private access to your personal knowledge base.
docsagent is the spec-driven MCP (Model Context Protocol) server that lets
any AI agent β Claude Desktop, Cursor, Cline, Qwen Code, or any MCP client β search, read, and
write your Zotero library, Obsidian vault, and Apple Notes (macOS) through a resident
C++ search engine. BM25 full-text search + query-ranked passage retrieval over 1,000+ PDFs
at ~15 ms, fully local (RAG-ready knowledge base).
/health probe).The shell never spawns the core during tool calls and never touches your source files. The core runs as a background service and stays available across MCP client restarts. Tool schemas and error codes: spec/.
Python shell (same verbs, under the core subcommand):
(core stop / core restart also available. The core indexes every configured source β your
Zotero data directory, your Obsidian vault, and (macOS) Apple Notes β and serves JSON-RPC on
http://0.0.0.0:23120/rpc.)
Claude Desktop / Cursor / Cline / Qwen Code (mcpServers):
Python shell (same tools, same contract, installed from this repo) β mcpServers:
Install the Python package first (step 1) so docsagent-mcp is on your PATH.
On startup the shell connects to the core, loads sources, and checks index status. If the core is not running it fails fast with startup instructions β it never spawns anything.
8 tools, 5 read + 3 write. Schemas are the single-sourced contract in
spec/tools/*.json (mirrored into both packages); arguments are validated
before handlers run and failures map to typed docsagent error codes.
list_sourcesEvery searchable source with capabilities, supported targets/includes/browse modes, filters, and document counts. Call this first.
Sources today: zotero (targets items, annotations, notes; collections/tags browse),
obsidian (a vault β notes as items, folders/tags browse), and apple-notes (macOS only β
the engine omits the source on other platforms). The vault is found at
~/Documents/Obsidian Vault (override with DOCSAGENT_OBSIDIAN_VAULT); Apple Notes is read
from the system Notes store (override with DOCSAGENT_APPLE_NOTES_DB).
searchCross-entry search over one source (items, annotations, and notes).
| Parameter | Type | Notes |
|---|---|---|
query | string | plain keywords or phrases; required unless mode=grep |
mode | relevance | grep | BM25 relevance by default; grep scans for a literal pattern without tokenization or ranking |
pattern | string, required when mode=grep | literal string to scan for |
caseSensitive, wholeWord, maxMatches | mode=grep only: ASCII case folding, [A-Za-z0-9_] word boundaries, hit cap total | |
target | "items" | "annotations" | "notes" or array | default items |
depth | ids | snippets | full | snippets by default (BM25-ranked passages) |
filters | object | tags, yearFrom/yearTo, itemType, authors, colors, containerId, titleContains |
k, snippetsPerResult, max_tokens | numbers | ranking depth and token budget (mode=grep: max documents, max hit windows per document) |
Returns results[] with global ids (zotero:KEY, obsidian:<path>, apple-notes:<uuid>),
titles, relevance, snippets; multi-target
searches group by target. In mode=grep each result carries matchCount and snippets[]
hit windows (hits[] with line/column/offset, and meta hits tagged with field),
relevance is 0, and the response adds totalMatches. Results are deduped (id, then
normalized title + year) and packed under a token budget.
search runs against config.defaultSource (default zotero). Mixed search is a core
capability: pass source: "all" to the core's search / grep methods and every source is
ranked independently, then fused with reciprocal rank fusion (k=60) β each hit is tagged
with its source. BM25 scores are not comparable across corpora, so fusion is rank-based.
get_contentRead one entry. mode=passages (query-ranked passages, k) or mode=fulltext
(offset pagination with nextOffset). Notes return their body with tags and metadata.
get_metadatainclude: metadata, abstract, annotations, notes, citation (bibtex / csljson /
formatted via citationFormat/citationStyle). Notes are packed under the token budget.
list_libraryBrowse modes: collections (drill-down via parentId), items (by containerId),
tags, saved_searches, standalone_notes. Browse modes are per source β Zotero exposes
all of these, while Obsidian and Apple Notes expose folders (drill-down) / tags / items.
| Tool | What it does | Key arguments |
|---|---|---|
import_item | Import local PDFs or resolve DOI / ISBN / arXiv IDs (via the Zotero translation server); optional autoClassify suggests collections | paths | identifiers, containerId, autoClassify, confirmed |
add_note | Add a Markdown child note to an item (converted to Zotero note HTML), with orphan verification and rollback | id, content, tags, confirmed |
batch_modify | Bulk add_to_collection / remove_from_collection / add_tags / remove_tags on up to 200 items in batches of 50 | action, ids, containerId, tags, confirmed |
Write tools target Zotero sources only β the Obsidian and Apple Notes sources are read-only.
Write safety gate (spec/algorithms/write-gate.md): layer 1 write tools are not
registered unless enableWrites=true; layer 2 confirmed=false returns a preview and
consumes no rate-limit quota; layer 3 confirmed writes consume a per-hour rate limit
(default 30/h). Anything above 20 items in batch_modify additionally reports
requiresConfirmation in the preview.
The C++ engine powers PapersGPT β the same index and retrieval stack ships in this MCP server. Benchmark on a real Zotero installation (full write-up):
| Metric | Mac (Intel i9) | Windows VM (4C8G) |
|---|---|---|
| Library size | 1,506 PDFs (4.5 GB on disk) | 500+ PDFs |
| Index build time | 141 s | a few seconds |
| Memory (agent process) | 227 MB | 160 MB |
| Average retrieval latency | ~15 ms | ~15 ms |
Config lives at ~/.docsagent/config.json (or $DOCSAGENT_CONFIG) β one file shared by
the JS shell, the Python wrapper, and the C++ core. Validated against
spec/config.json.
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