# apple-notes-cli Search, read, and export Apple Notes from the terminal by reading the local Notes database directly — no AppleScript, no UI automation, no cloud API. Built for the common case: **you mostly want to look things up, not write them.** Recalling what you noted about a project, finding the meeting where a decision was made, pulling every note that mentions a library — that is read-heavy work, and it is exactly where the existing tooling is weakest. ```console $ apple-notes search "kubernetes" -n 3 4821 2026-09-08 14:02 Work/Infra/Cluster upgrade notes (7x) …drain the node before the kubernetes control plane restarts… 3907 2026-08-30 09:15 Work/Runbooks/On-call (2x) …kubernetes events are the fastest way to see why a pod is pending… $ apple-notes recent --since 2d 4830 2026-09-09 15:59 Work/Meeting notes 4829 2026-09-09 13:54 Personal/Reading list ``` ## Why not AppleScript Almost every Apple Notes integration drives Notes.app through AppleScript (`osascript`): the [`memo`](https://github.com/antoniorodr/memo) CLI does — its `get_memo.py` and `id_search_memo.py` shell out to it — as do the [`apple-notes` skill in OpenClaw](https://github.com/openclaw/openclaw/blob/main/skills/apple-notes/SKILL.md) and Hermes, which wrap `memo`, and Claude's own desktop [Notes connector](https://support.claude.com/en/articles/11176164-use-connectors-to-extend-claude-s-capabilities). AppleScript is the right choice for *writing* — it is Apple's supported interface and it keeps CloudKit sync intact. But for reading it carries costs that are easy to miss. Measured on a real 818-note store: | Operation | AppleScript | apple-notes-cli | | --- | --- | --- | | Enumerate folders and count notes | 1.85 s | — | | Fetch one note body | 0.325 s | — | | **Full-text search every note** | **~266 s** (extrapolated) | **0.11 s** | **Full-text search is impractical, so tools quietly stop doing it.** `first note whose id is "…"` is an unindexed linear scan inside Notes.app, so each body costs about a third of a second. Reading all 818 would take over four minutes. Faced with that, `memo` searches **titles only** — its `search_memo.py` builds a `{title: id}` map and fuzzy-matches against the keys, never the bodies. So `memo notes -s "kubernetes"` finds notes *called* "kubernetes", not the notes that discuss it. The OpenClaw skill exposes this as "fuzzy search" with no indication that note contents are not searched. **Caching trades freshness for speed, usually silently.** `memo` caches its note list to `~/.cache/memo/notes_cache.json` with a 300-second TTL, so a note you just wrote can be invisible for five minutes. Neither the skill documentation nor the CLI surfaces this, so an agent asking "what did I note today?" can be handed a confidently stale answer. **Other friction that comes with the AppleScript path:** - **It needs Notes.app.** The app gets launched or scripted in the background, and if it hangs or shows a modal, the integration hangs with it. - **It needs Automation permission** (System Settings → Privacy & Security → Automation), granted interactively per client app. That makes unattended use — cron, CI, an SSH session — awkward or impossible. - **Bodies arrive as HTML**, so every tool bolts on an HTML-to-Markdown converter and inherits its fidelity bugs. - **macOS only**, and it cannot run from the web or iOS at all. - **Per-note round trips.** Reading N notes means N `osascript` invocations, each paying process startup plus Apple Events IPC. Reading the SQLite store sidesteps all of it: one query, then in-memory decoding. Full-text search over everything takes ~0.11 s, which is why this tool needs no cache and always reflects the live database. The trade-off is that this only reads; AppleScript remains the right way to create and edit notes. The two compose well — see [Reading is all it does](#reading-is-all-it-does). ## Install Requires macOS and Python 3.10+. ### Just ask your agent If you use Claude Code, Claude Desktop, or any coding agent, point it at this file and it has everything it needs: > Read https://github.com/ingjieye/apple-notes-cli/blob/main/README.md and set > it up, including the skill. ### The CLI ```bash uv tool install git+https://github.com/ingjieye/apple-notes-cli # or pipx install git+https://github.com/ingjieye/apple-notes-cli ``` Run it straight from a clone without installing: ```bash git clone https://github.com/ingjieye/apple-notes-cli && cd apple-notes-cli uv run python -m apple_notes_cli recent ``` macOS may ask you to grant your terminal access to the Notes container the first time. Nothing here needs Full Disk Access on its own. ### The agent skill [`skills/apple-notes/SKILL.md`](skills/apple-notes/SKILL.md) teaches an agent to use this CLI — when to reach for it, how to page from search results to full note bodies, and what its limits are. Drop it in place: ```bash mkdir -p ~/.claude/skills/apple-notes curl -fsSL https://raw.githubusercontent.com/ingjieye/apple-notes-cli/main/skills/apple-notes/SKILL.md \ -o ~/.claude/skills/apple-notes/SKILL.md ``` Use `.claude/skills/` inside a project instead of `~/.claude/skills/` to scope it to that project. Then ask your agent things like "what did I note about the cluster migration?" or "找一下我记过的会议决定".
Setup steps, if you are an agent reading this ```bash # 1. macOS only; bail out early elsewhere. [ "$(uname)" = "Darwin" ] || { echo "macOS required"; exit 1; } # 2. Install the CLI (uv preferred, pipx as fallback). if command -v uv >/dev/null; then uv tool install git+https://github.com/ingjieye/apple-notes-cli else pipx install git+https://github.com/ingjieye/apple-notes-cli fi # 3. Install the skill. mkdir -p ~/.claude/skills/apple-notes curl -fsSL https://raw.githubusercontent.com/ingjieye/apple-notes-cli/main/skills/apple-notes/SKILL.md \ -o ~/.claude/skills/apple-notes/SKILL.md # 4. Verify against the real store. Exit 1 from `search` just means no match. apple-notes folders | head -5 apple-notes recent -n 3 ``` If step 4 reports the database is missing, Notes.app has never been launched on this machine. If it raises a permission error, the terminal needs access to the Notes container — that is a macOS prompt the user has to accept, not something you can grant.
## Commands ``` apple-notes search full-text search across every note body apple-notes recent list recently modified notes apple-notes show print one note as Markdown apple-notes folders list folders with note counts apple-notes export export everything to Markdown files ``` ### search ```bash apple-notes search "OpenTelemetry" apple-notes search "TODO|FIXME" --regex apple-notes search "invoice" --folder Finance --since 1w apple-notes search "postgres" --json | jq -r '.[].title' apple-notes search "draft" --body-only --no-snippets ``` Results rank by match count, then by recency. Titles are searched alongside bodies unless you pass `--body-only`. `--json` emits structured records, which is the useful shape for piping into an LLM or another tool. ### recent ```bash apple-notes recent -n 50 apple-notes recent --since 6h --folder Work ``` Metadata only — bodies are never inflated, so this stays fast regardless of store size. ### export ```bash apple-notes export ~/Downloads/notes apple-notes export ~/Downloads/notes --incremental ``` One Markdown file per note, mirroring your folder tree, with YAML frontmatter (title, ids, dates, folder, links, attachments, and a `notes://` link back to the note). Attachments are copied next to the Markdown under `attachments//`. `--incremental` keeps a manifest so unchanged notes are skipped and exports of deleted notes are pruned. ## How it works ``` NoteStore.sqlite └── ZICNOTEDATA.ZDATA gzip → protobuf → text runs → Markdown └── ZICCLOUDSYNCINGOBJECT titles, dates, folder tree, attachments ``` | Module | Role | | --- | --- | | `store.py` | read-only SQLite access, folder tree, attachments | | `parser.py` | gzip + protobuf decoding, Markdown rendering | | `search.py` | search, recency listing, single-note reads | | `export.py` | Markdown output and the incremental manifest | Three details are worth knowing if you build something similar: **Open the database with `mode=ro`, never `immutable=1`.** The `immutable` flag makes SQLite skip the `-wal` file, which silently serves a stale snapshot missing your most recent notes. On a live store the `-wal` file routinely holds megabytes of un-checkpointed data. WAL mode allows concurrent readers, so `mode=ro` is safe while Notes.app is running and never blocks it. Export uses SQLite's `backup()` API instead, for a stable point-in-time copy. **There is no FTS index.** The schema has no full-text tables, and bodies are gzipped protobuf blobs, so `WHERE body LIKE …` is not available. Search means inflating every candidate body and matching in memory. At ~800 notes that is about 30 ms, so this tool does no caching and always reflects the live store. **Recently Deleted is `ZFOLDERTYPE = 1`.** Notes in the trash keep `ZMARKEDFORDELETION = 0`, so filtering on that column alone still surfaces them. Matching on the folder type is also language-independent, unlike comparing against a localized "Recently Deleted" string. They are excluded by default; pass `--include-trashed` to include them. ## Exit codes `search` follows the `grep` convention: `0` when something matched, `1` when nothing did, `2` on a bad argument or an unreadable database. That makes it usable in a conditional: ```bash if apple-notes search "release checklist" --no-snippets >/dev/null; then echo "found it" fi ``` ## Reading is all it does This tool only reads. It never writes to `NoteStore.sqlite` — modifying the store directly would corrupt CloudKit's sync state and risk losing notes. If you need to create or edit notes, drive Notes.app through AppleScript for the write path and use this for reading. Password-protected notes are listed but their bodies stay encrypted and unreadable; they are skipped unless you pass `--include-password-protected`. ## Development ```bash uv run python -m unittest discover -s tests ``` `tests/test_parity.py` is the original single-file exporter's suite, kept unchanged apart from neutralized example URLs, so it guards the protobuf decoding against regressions. `tests/test_search.py` builds a synthetic Core Data store to cover the query layer, trash handling, and time filters. ## License MIT