MCP server: gym attendance & trainer analytics from existing cameras
View on GitHub ↗Homepage ↗GymCam turns the cameras a gym already has into automatic attendance and trainer-performance analytics — no new hardware, no check-ins.
Feed it the existing CCTV stream and the class schedule; it recognizes trainers, counts attendees per class, and reports what's actually happening: which classes are full, which are dead, and which trainers fill the room.
Gym owners run on gut feeling. Booking software (Mindbody, Glofox) only captures check-ins — and people skip check-ins, so the data is incomplete. Hardware people-counters (Density, V-Count) cost thousands and count bodies without context.
GymCam reuses what's already in the building and maps counts to classes and trainers — the thing that actually drives revenue.
- Today's summary — classes held, total attendance, top classes - Trainer attendance — daily/weekly fill rate and no-show rate per trainer - Class performance — every class ranked by fill rate, so dead classes are obvious - Revenue insights — most profitable vs. least profitable classes
- Zero install — cameras already do the counting (security cameras are required in nearly every country). No sensors, no mounting, no new hardware. - No check-in friction — stop making members do a meaningless task; people just show up. - Class truth — which classes are full and which are dead, not the paper log anyone can fudge. - Trainer accountability — real fill rate + no-shows per trainer; the "16 becomes 20" rounding dies. - Occupancy & density — overfull classes and cramped rooms are a pricing / scaling / staffing signal. - Room optimization — see the big room idle whi
From the project README.
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