Show HN: Personal rolodex using beeper MCP and Memory Store (shubhamattri.com)

Shubham reports using Beeper’s MCP integration with Memory Store — an “active memory” MCP server — to unify conversations and context across WhatsApp, Slack, Telegram, code editors (Zed, VS Code), AI tools (Claude, ChatGPT), Raycast and meeting transcriptions (Granola). By plugging Memory Store into Beeper mid‑October he now has a single, tool‑agnostic memory layer that autonomously links past messages, meeting notes and code context so he can draft context‑aware replies and pull up relevant history without manually hunting through different apps. The technical significance is that Memory Store acts as a persistent MCP server-side memory layer rather than a siloed note store: it creates and surface connections across heterogeneous data sources, making LLM-assisted workflows materially more productive for people who constantly switch between code and conversations. For developers this means faster, more accurate context retrieval (e.g., reply drafting, linking meeting transcripts to projects) and less cognitive overhead maintaining separate systems. Memory Store is in private beta; developers using Beeper can join the waitlist at memory.store or DM Shubham for access.