Alternative · Comparison
Looking for a Granola alternative that keeps audio on your Mac?
Daisy is an open-source, local-first meeting recorder for macOS. Audio never leaves your machine, transcription runs on the Apple Neural Engine, summaries use your own AI key, and a local MCP server lets Claude Desktop or Cursor query your transcripts without a round-trip through anyone’s cloud.
Free during beta · Lifetime after launch · Apple Silicon (M1+) · macOS 14+
Daisy vs Granola at a glance
| Feature | Daisy | Granola |
|---|---|---|
| Audio recording happens | On your Mac | On Granola's servers (uploaded) |
| Transcription | On-device (Whisper, Apple Neural Engine) | Cloud |
| AI summary | Bring your own key (Anthropic, OpenAI, Apple Intelligence, local Ollama via MCP) | Granola's own AI (closed) |
| Open source | Yes — Apache 2.0 | No, closed SaaS |
| Pricing | Free during beta · one-time lifetime purchase after launch | $18/user/month (Business plan) |
| Bot joining the call | Never — local capture only | Optional bot |
| Works offline | Yes (after first model download) | No, cloud-dependent |
| MCP server for AI clients | Yes — Claude Desktop / Cursor / Cline / any MCP client | No |
| Destinations | Notion / Linear / Attio / webhook / your folder (Obsidian, iCloud) | Granola's own library + Notion / Slack |
| Speaker diarization | On-device (Pyannote, CoreML) | Cloud |
| Storage | Your folder on your disk — plain `.md` + `.caf` files | Granola's cloud, indexed by Granola |
| Telemetry | None | Standard SaaS analytics |
| Platforms | macOS 14+ (Apple Silicon) | macOS, Windows, iOS, web |
Where the difference matters
Granola is a strong product if you're OK with audio leaving your Mac and living in someone else's database. Daisy is for the case where that's not OK — regulated industries (legal, medical, finance), people doing customer or research interviews that touch sensitive data, founders talking to candidates about offers, anyone who's signed an NDA with anyone they record with. Architecturally Daisy never sends audio anywhere. Granola promises to handle it carefully; both can be true at once, and you pick based on which you're more comfortable with.
Where Granola is ahead
Multi-platform — Granola runs on Windows, iOS, web, not just Mac. If you take meetings on more than your MacBook, that's a real thing Daisy doesn't solve today. Granola also has a more polished onboarding and a longer track record. Daisy is the right choice when you'd trade those for local-first + open source + a one-time purchase.
Pricing model
Granola is $18/user/month on the Business plan. That's $216/year per seat, indefinitely. Daisy is free during beta and one-time lifetime after launch — no monthly subscription, no per-meeting fees, no fees scaled to how much you record. If you're using meeting notes 50+ times a month for a few years, this difference compounds.
Open source
Daisy is Apache 2.0 on GitHub — you can read every line, build from source, audit the network calls, run a fork. Granola is closed SaaS, which means the privacy claims have to be taken on trust. Both can be defensible positions; if open source matters to you, only one of the two is open source.
Why MCP matters
Daisy runs a local MCP server, so Claude Desktop, Cursor, Cline, and any other MCP-compatible AI client can query your meeting transcripts directly — no cloud round-trip, no API key shared with Daisy, no "Ask Daisy" closed garden. This is the standout structural difference in our category right now. If you spend your day in Claude Desktop and want it to know what you talked about in your 1-on-1s, Daisy is built for that out of the box; nobody else in the space is.
Try Daisy
Free during beta. Download the signed DMG, drop it into Applications, grant microphone + screen-recording permissions on first launch, and start recording. No account, no email wall, nothing to sync.
Comparison written by the Daisy team. Granola positioning verified against granola.ai as of May 2026. If anything is out of date or wrong, open an issue at github.com/addicted-studio/daisy-app/issues and we’ll fix it.