daisy-app

# Daisy A local-first meeting recorder, push-to-talk dictation tool, and AI-notes app for macOS — with a local MCP server so Claude Desktop and Cursor can query your transcripts without anything leaving the Mac. [](https://ko-fi.com/G3W723TUZD) Daisy captures meeting audio (microphone + system-audio loopback via ScreenCaptureKit), transcribes it on-device with Whisper on the Neural Engine, and produces a structured outline with action items and a draft follow-up. Audio and transcripts never leave the Mac unless you explicitly enable a remote summary provider. Remote summaries can use your own API key or an explicitly connected ChatGPT account; an optional on-device privacy filter pseudonymizes detected sensitive data before supported cloud requests. End-user installation, FAQ, and the privacy story live at **<https://mydaisy.io>**. This README is for people building Daisy from source. ## What it does Three capture modes, one app: - **Meetings** — records both sides of a call (your mic + the other side via system-audio loopback), no bot joining the meeting. On-device transcription + diarization (`Remote A` / `Remote B`, with optional mic-side attribution), a summary, action items, and a draft follow-up. Optional extras include periodic screenshots with on-device OCR, a preparation brief built from the agenda and past sessions, evidence-backed progress against the meeting plan, local meeting analytics, and custom meeting apps beyond the built-in list. - **Push-to-talk dictation** — hold a hotkey, speak, and the text is pasted at your cursor in any app. Three on-device engines: Whisper (default), Parakeet (FluidAudio) for lower latency, and Apple SpeechAnalyzer on macOS 26 (zero download). A custom-vocabulary dictionary fixes names/jargon, an optional voice profile learns your phrasing, and a rolling 24-hour history lets you re-copy. - **Voice notes** — quick one-off thoughts saved to your Library. Optional: import existing **Apple Voice Memos** as flat transcripts (on-device, opt-in, needs Full Disk Access). Around the edges: morning and end-of-day summaries on Home, an opt-in keyboard-layout auto-fixer (retypes text entered in the wrong layout, with undo and per-app exceptions), and provider-returned ChatGPT plan-window usage plus local token accounting for API providers. The UI is localized in English and Russian. The differentiator: Daisy ships a **local MCP server** bound to `127.0.0.1` that exposes your sessions as a queryable, actionable data source to any MCP client (Claude Desktop, Cursor, Codex). Because the transcript is already local, Daisy can be a local-only MCP source — something cloud meeting tools structurally can't offer. ## Status - Latest release: see [`scripts/release-notes/`](./scripts/release-notes/) and <https://mydaisy.io/appcast.xml>. Beta ships from `main`; stable is promoted from a soaked beta (see [`RELEASING.md`](./RELEASING.md)). - Deployment target: macOS 14 Sonoma. The Apple Intelligence summarizer and the Apple SpeechAnalyzer dictation engine require macOS 26 Tahoe; everything else runs on 14+. - Apple Silicon (M1+). Signed with Developer ID, notarized, stapled, Sparkle EdDSA-signed for in-app updates. - License: **Apache 2.0** (see [`LICENSE`](./LICENSE)). Full public source — build it and verify there's no telemetry. ## Build from source Requirements: - Xcode 26+ (ships the macOS 26 SDK the project builds against) - An active Apple Developer account if you want a signed local build (unsigned builds are fine for development inside Xcode) Clone and open: ```bash git clone https://github.com/ca33u/daisy-app.git cd daisy-app open Daisy.xcodeproj ``` The Swift Package Manager dependencies (Sparkle, WhisperKit via [`argmax-oss-swift`](https://github.com/argmaxinc/argmax-oss-swift), FluidAudio) resolve on first project load. Hit Run; the app launches. ## Project layout ``` Daisy/ → SwiftUI app sources (PBXFileSystemSynchronizedRootGroup) DaisyTests/ → unit tests Benchmarks/ → reproducible WER/DER/JER scorer, product runner, and public evidence Daisy.xcodeproj/ → Xcode project scripts/ release.sh → end-to-end release: archive → notarize → DMG → sign → Sparkle appcast release-notes/ → per-version markdown bullets consumed by release.sh dmgbuild_settings.py → dmgbuild config (Python) for the installer DMG assets/ → DMG background, app icons build/ → archive output (gitignored) RELEASING.md → branch/channel model and the release/promote/hotfix flows ``` Key services that drive the app: - `CoreAudioMicRecorder` — CoreAudio mic capture with route-change recovery and the archive `.caf` writer (replaced the old AVAudioEngine tap to fix route-change/Bluetooth dropouts) - `SystemAudioCapture` — `SCStream` loopback for the remote side of a meeting, Bluetooth-output detection, silent-capture warnings - `Transcriber` / `WhisperEngine` — WhisperKit on-device transcription with a Silero VAD pre-pass - `ParakeetEngine` / `AppleSpeechEngine` — the two alternative dictation engines: FluidAudio Parakeet-TDT (low latency) and Apple SpeechAnalyzer (macOS 26, no model download); Whisper is the default - Diarization + speaker memory — FluidAudio (Pyannote) labels remote voices; named speakers are remembered locally by a short voice fingerprint - `DictationPaste` — pastes dictated text at the cursor via the Accessibility API, restoring your prior clipboard - `RecordingSession` — orchestrates a session, owns calendar binding and auto-stop scheduling - `Summarizer` — multi-provider LLM dispatch: Apple Intelligence (on-device), ChatGPT account, Anthropic, OpenAI, Kimi (Moonshot), Cursor API key, Ollama, LM Studio (local), or an MCP summarizer - `SensitiveDataProtector` — optional on-device pseudonymization/redaction boundary for supported remote summaries - `MeetingPreparation` / `MeetingPlanAnalysis` / `MeetingAnalytics` — pre-meeting context, evidence-backed agenda progress, and local call metrics - `ScreenshotCapture` — opt-in periodic screenshots of the meeting window with Vision OCR; screen text flows into the transcript and summary - `PreMeetingBrief` / `MorningBrief` / `EndOfDaySummaries` — local briefs assembled from your calendar and past sessions, plus an evening digest - `VoiceProfile` — opt-in personalization learned from your dictations (and, optionally, your mic side of meetings) - `LayoutAutoFix` — opt-in keyboard-layout auto-correction via a CGEvent tap, with undo and per-app exceptions - `TokenLedger` — local token-usage accounting per cloud provider, shown on Home - `MCPServer` — the local MCP server on `127.0.0.1`; exposes nine tools (five read, four act) to Claude Desktop / Cursor / Codex - `VoiceMemoScanner` / `VoiceMemoIngestor` — opt-in, on-device import of Apple Voice Memos to Markdown transcripts - Sparkle 2 — in-app auto-updates against `https://mydaisy.io/appcast.xml` ## MCP server Daisy's MCP server turns your recordings into a live data source for AI clients, entirely on-device. Enable it in **Connections → MCP server** and use the one-click setup for Claude Desktop, Cursor, or Codex — the config is written for you. Nine tools, scoped to safe, reversible operations (no deleting, no editing transcript bodies): - **Read** — `list_sessions`, `get_session`, `search_sessions`, `list_folders`, `list_destinations` - **Act** — `resummarize_session`, `set_session_title`, `rename_speaker`, `route_session_to_destination` (Notion / Linear / Slack / webhook) Docs: <https://mydaisy.io/docs/mcp>. ## Reproducible benchmarks [`Benchmarks/`](./Benchmarks/) contains the product-pipeline runner, a neutral standard-library scorer for WER/CER/DER/JER, fixtures, and published raw evidence. The first public baseline is AMI `ES2004a`: Daisy 1.0.7.59 detected 4/4 speakers with 15.68% DER and 20.28% JER at a median 0.122× real time across three warm runs on an M4 MacBook Air. It is one reproducible diarization case, not a general accuracy claim; Humla and OpenWhispr remain unscored until their raw output exists for the exact same audio. See the [methodology and publication gate](./Benchmarks/README.md) and the [public evidence](./Benchmarks/reports/public/). ## Release flow ```bash DAISY_AUTO_PUSH=1 ./scripts/release.sh <shortVersion> <buildNumber> [stable|beta] ``` Beta is the default channel from `main`; stable is promoted from a soaked beta with `./scripts/release.sh promote <version>` (no rebuild). Six steps: archive → export → notarize → DMG → publish to the [daisy-web](https://github.com/ca33u/daisy-web) repo → inject an `<item>` into `appcast.xml` and commit. Vercel auto-deploys the site within a couple of minutes. Full branch/channel model and the hotfix flow are in [`RELEASING.md`](./RELEASING.md). Release notes for each version go in `scripts/release-notes/<shortVersion>.md` as a flat markdown bullet list (`- one line per change`). The script extracts those bullets and embeds them in the appcast `<description>` so Sparkle shows them in its update sheet. ## Support and contact - Chat with the community → [Discord](https://discord.gg/JYCZRZXy6j) - Questions, ideas, show-and-tell → [GitHub Discussions](https://github.com/ca33u/daisy-app/discussions) - Product issues, feature requests → file an issue on this repo or email **support@mydaisy.io** - Security disclosures → see [`SECURITY.md`](./SECURITY.md) - Procurement / security review / tailored deployment → email **hello@mydaisy.io** - End-user docs → <https://mydaisy.io/docs> · Privacy → <https://mydaisy.io/privacy> ## Credits - [Sparkle](https://sparkle-project.org) — in-app auto-updates - [WhisperKit](https://github.com/argmaxinc/argmax-oss-swift) by Argmax — Apple Silicon Whisper inference (part of the Argmax OSS SDK) - [FluidAudio](https://github.com/FluidInference/FluidAudio) — Parakeet ASR + speaker diarization - [FoundationModels](https://developer.apple.com/documentation/foundationmodels) — on-device summarization via Apple Intelligence (macOS 26+) ## License [Apache 2.0](./LICENSE).