Local AI memory layer for developer context

What to build

A lightweight Mac menu-bar app for solo developers that continuously records screen activity and meeting audio, transcribes and indexes it locally, and exposes that history as searchable context to AI coding assistants (Claude Code, Cursor, Codex) via an MCP server.

AI coding assistants forget everything between sessions, forcing developers to re-explain context every time; a local-first recorder that turns a dev's own screen and meeting history into MCP-queryable memory removes that friction.

Demand

Solo developers and small teams using AI coding tools daily are the buyers, and demand is rising now because MCP has standardized how tools like Claude Code and Cursor pull in external context, making a 'memory layer' integration newly practical to ship and adopt.

• Hacker NewsLaunch

  Show HN: Breadcrumb, record everything on your mac + context manager for AI — 17 points, 2 comments on HN.

• Rewind / LimitlessAdjacent product

  Rewind (now Limitless) built a paid product around the same core idea of recording everything on a Mac for personal recall, showing willingness to pay for local activity capture.

• ScreenpipeAdjacent product

  Screenpipe is an open-source 24/7 screen and audio recorder built specifically to feed context to AI agents, validating demand for recorder-plus-AI-context tooling among developers.

Stack

• Swift + ScreenCaptureKit (macOS screen capture)
• whisper.cpp or Apple Speech framework (local transcription)
• SQLite + local vector embeddings (sqlite-vec or similar) for search index
• Model Context Protocol (MCP) server SDK
• Core Data or local filesystem for encrypted storage
• Sparkle (auto-updates) for distribution

Solo + AI difficulty

The hardest parts are reliable low-overhead continuous screen capture plus fast local transcription and indexing without killing battery or disk; the MCP server layer itself is comparatively easy since the protocol is simple and well-documented. A focused solo builder using AI coding tools could get a rough MVP (record, transcribe, basic search, one MCP tool) working in 4-6 weeks, with most of the remaining time going into privacy controls (pause/redact) and making retrieval actually relevant.

Entry threshold

Core pieces (screen capture, local transcription, SQLite storage, MCP server) are buildable solo with existing open-source models, but matching this project's polish (meeting diarization, rules engine, 30+ MCP tools) likely takes weeks to a couple of months rather than a weekend.

Window

6-12 months

Where to find first users

• Show HN launch (follow up post or similar tools)
• Cursor and Claude Code Discord/community channels
• r/indiehackers and r/SideProject
• Product Hunt launch targeting developer tools category

Competitors

• Rewind (Limitless)
• Screenpipe

Counter-signals & risks

• Continuous screen and meeting recording raises significant privacy, data-security, and legal/compliance concerns, including recording third parties without consent and storing sensitive credentials or proprietary code.

• Local storage and indexing of full screen history can be resource-intensive on disk and CPU, creating adoption friction compared to simpler manual context-sharing workflows.

• The space is already crowded with memory/recall tools like Rewind and Screenpipe plus native OS features, so differentiation and a defensible moat are uncertain.

• Only a single Show HN data point (17 points, 2 comments) exists so far, with no historical match data, leaving market demand and retention unproven.