Your next session should know what happened.

Conversation history is a poor handover. A context window fills, a session ends, or another agent takes over. Useful decisions disappear into transcripts, while repeatedly loading everything costs attention and context. Search alone also leaves a gap: a vaguely similar passage is not the same as the reason a particular change was made.

Our earlier operator work separated daily observations from durable references and learned rules. MemIndex develops that continuity problem into a product for coding work. We needed capture, retrieval, inspection and recovery to work together, without asking someone to become a full-time archivist for their assistant.

We built it for developers who work with coding agents over days rather than one conversation, and for teams that need shared project memory across machines. The practical question is familiar: why are we explaining the same architecture, rejected approach or deployment decision again? MemIndex gives the next session somewhere to start and a way to investigate the history when the short summary is not enough.

We built integrations that capture supported agent activity, a service that turns that activity into concise notes and session summaries, and a viewer for browsing what was retained. Notes carry project and session context. Supported integrations can bring relevant context into later sessions; search tools let an agent retrieve older work deliberately.

We also built the surrounding controls: export and import, project exclusions, optional secret filtering, work-state tracking, and local snapshots with a restore command. Managed hosting puts central memory on a service we run. A self-run server gives operators responsibility for their storage, model service, access keys, HTTPS and backups.

Activity arrives through an agent's session events or saved conversation files, depending on the integration. A chosen model service writes the memory notes. Retrieval starts with a short list of matches, expands into the surrounding timeline, and fetches full notes when needed. Local search can match meaning and words; the remote server tools use word search.

We keep the differences between integrations explicit. A client that can search existing memory does not automatically capture new work. Endless Mode helps local Claude Code sessions continue after compaction; it does not recreate missing replies or apply to every agent. Local storage also does not mean all processing is offline: the configured note-writing model receives the captured activity.

Persistence raises the standard for recovery. After a real loss exposed the absence of a backup engine, we built consistent snapshots that can run while the database is being written. Restore must handle database sidecars and derived search state, preserve an unfinished-restore marker when search is unavailable, and reject a newer schema before touching an older installation.

Trust also means being able to inspect and remove memory. Private tags filter saved notes rather than every possible copy of a conversation, and deletion has to account for exports, pending files and backups. We make those boundaries visible. The outcome is a useful working record with explicit limits, rather than a promise that an agent remembers everything perfectly.