# Hemory

> Hemory is an always-on listening app that captures every conversation into a private, searchable memory and connects it to your AI agents via MCP.

Hemory is a mobile-first app built by a small team at ONES.com that continuously listens to your real-world conversations, transcribes them, and stores them as a private, searchable memory vault. It connects that memory to AI agents through a standard MCP server, letting agents like Claude Code, Codex, and Cursor answer questions grounded in what you actually said and heard. The app is currently available on iOS and Android, with macOS, Windows, Linux, web, and self-host options listed as coming soon.

## What It Is

Hemory sits in the "agent memory" category — it is not a meeting recorder or note-taking app, but a persistent, always-on memory layer for AI agents. The core loop is: Hemory listens on your phone or Apple Watch, transcribes audio using voice-activity detection (VAD) so silence never counts against your quota, organizes sessions into a timeline of activity types, and exposes the resulting memory to any MCP-compatible agent via a `search_memory` tool. The name is a portmanteau of "Hear" and "Memory," reflecting the mission stated on the About page: "Remember everything you said and heard — lossless context, ready for AI."

## How the Listening Pipeline Works

Hemory processes audio in a multi-stage pipeline entirely designed around privacy and usability:

- **VAD metering** — only moments when someone is actually speaking count against listening hours; silence, gaps, and background noise are filtered out.
- **Auto-transcription** — sessions are transcribed in up to 100 languages, then run through an AI cleaning pass for readability.
- **Activity segmentation** — the day is automatically split into six types (meeting, work, meal, social, learning, chit-chat) based on conversation content, with no manual tagging required.
- **Type-aware summaries** — meetings get structured minutes with agenda, decisions, and action items; casual meals get a light note.
- **Speaker recognition** — voices are identified across sessions; users name a speaker once and all past and future sessions update.

## MCP Integration and Agent Connectivity

The MCP server is a first-class feature. Hemory exposes a `search_memory` tool that any standard MCP client can call. Setup is a single terminal command (`codex mcp add hemory` or `claude mcp add hemory`). The homepage demonstrates the workflow: an agent receives a prompt like "what did Daniel promise me in last Tuesday's sync?", calls `hemory.search_memory`, and returns a grounded answer from the transcript. The same connection can be used to generate documents — monthly work reports, PRDs from customer interviews, nightly journals — all from the memory Hemory has accumulated.

Supported agents listed on the site include Claude Code, Codex, Gemini, Cursor, VS Code, OpenClaw, and Hermes, plus any other standard MCP client.

## Privacy Architecture

Hemory's privacy model is a core design constraint, not an afterthought:

- Raw audio is never stored in the cloud — it is processed as a stream and destroyed after transcription.
- Audio stays only on the listening device and is never synced across devices.
- Hemory states it never uses audio, transcripts, or voice data to train or improve any AI model.
- A self-host option is listed as coming soon for users who want to run the entire stack on their own infrastructure.
- Listening can be set to manual mode (user-initiated) or scheduled mode (e.g., weekdays 9:00–18:00) to keep the privacy boundary explicit.

## Apple Watch Support

Hemory runs natively on Apple Watch, which the team positions as the most natural listening device — closer to the speaker than a phone. The Watch captures and uploads audio independently. The site claims up to 10 hours of listening on Apple Watch Ultra 3 / Series 11 with no more than 30% extra battery usage, and listening automatically pauses during calls and resumes afterward.

## Current Status and Platform Roadmap

Hemory is actively available on iOS (App Store) and Android (direct APK download). The homepage and features page both list macOS, Windows, Linux, web app, and self-host as "coming soon." The product is made by a small team at ONES.com and ships in 9 UI languages with transcription support for 100 languages. Community channels include a subreddit (r/Hemory), Twitter/X (@hemory_com), and a Discord server.

## Features
- Always-on ambient listening with VAD metering
- 100-language transcription with AI cleaning pass
- Auto activity segmentation (meeting, work, meal, social, learning, chit-chat)
- Type-aware summaries and meeting minutes
- Speaker recognition by voice across sessions
- Built-in Q&A agent grounded in transcripts
- MCP server for connecting to external AI agents
- Apple Watch listening support
- Scheduled and manual listening modes
- Zero cloud audio retention — audio processed and destroyed after transcription
- Self-host option (coming soon)
- Multi-turn agent conversations over MCP

## Integrations
Claude Code, Codex, Gemini, Cursor, VS Code, OpenClaw, Hermes, Apple Watch, MCP-compatible agents

## Platforms
WINDOWS, MACOS, LINUX, ANDROID, IOS, API, VSC_EXTENSION

## Pricing
Freemium — Free tier available with paid upgrades

## Links
- Website: https://www.hemory.com/?utm_source=producthunt
- Documentation: https://www.hemory.com/docs/
- EveryDev.ai: https://www.everydev.ai/tools/hemory