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MLH: Best Use of MongoDB Atlas

Workspaces and their operation log, change-stream live sync with the phone, hybrid search, time series, vector memory and a guarded MCP server.

Atlas holds the people side: workspaces, their operation logs, live sync, memory and search over past work.

Feature Why it is a real use
Documents with a unique (workspace, seq) index An optimistic lock: two writers cannot both append operation n.
Multi-document transactions A person’s operation and what it taught the agent land together.
Change streams Live sync between server processes, browsers and the phone: a door width typed on the phone reaches the desktop in about a second.
$jsonSchema validation The append-only log refuses a malformed entry.
TTL index Read-only share links delete themselves.
Atlas Search (fuzzy, facets, highlights) Search past investigations with counts by tool, status and city.
Vector Search with filters, automated embedding (voyage-4) Recall similar past needs per persona, with no embedding key in the app.
Hybrid search with $rankFusion “Could not roll a chair into the toilet” finds “No ADA clearance at the toilet”.
Time series collection Every phone reading (GPS, altitude, tilt, sound) as one measurement; the timeline groups by minute with $dateTrunc.
2dsphere and $geoNear Shortlisted buildings near a point.
LangGraph checkpointer and store Paused agent turns and long-term memory next to the workspaces.
MongoDB MCP server (read-only, guarded) The agent counts and groups over the person’s own past work.

Scripted flow: web/src/skins/app/demo/flows/mongodb.json, “Live sync between two windows, then search past work”.

Demo path. Pair the phone by QR, type a door width on the phone, watch it land on the desktop; Copy link opens a read-only shared workspace; search past work for a phrase that is not in it word for word.

In the docs