PAP Analytics MCP
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
pap-analytics-mcp
Device-agnostic analytics over PAP (CPAP/APAP/BiPAP/ASV) therapy data, exposed to AI agents as an MCP server.
Ask an agent "How was last night?", "Analyse 02:10–02:40", "Compare this week with last week" – the agent calls small, aggregate-first tools instead of reading raw waveforms.
raw device data ──► vendor adapter ──► canonical PAP model ──► store ──► analytics ──► MCP tools
(ResMed SD card / (ResMed now, (vendor-neutral) (DuckDB + (stdio / HTTP)
AirCANnect SMB share) Löwenstein later) Parquet)Sources (v1): ResMed AirSense/AirCurve 10/11 SD-card layout (
Identification.*,STR.edf,DATALOG/). The AirCANnect SMB share uses the same layout, so a real SD card and the share both work.Later: Löwenstein (prisma) and other vendors through the same adapter contract.
Runs: locally (
uv) or in Docker, read-only over the source data.Not a medical device. Output is analytical, not a diagnosis.
Status
Scaffold only. Implementation follows the work packages in docs/plan/; progress is tracked in Multica (project PAP Analytics MCP).
Related MCP server: sleepon-mcp
Quick start (development)
uv sync
uv run pytest # quality gate (also run in CI)
uv run ruff check .
uv run pap --helpReal test data (the author's own nights, published on purpose) lives in tests/data/.
Documentation
File | Content |
Rules for humans and coding agents working in this repo | |
Stable shape: components, canonical model, contracts, invariants | |
Append-only decision log (ADR) | |
Implementation plan split into self-contained work packages | |
Real-data fixture description and known facts |
License
MIT – see LICENSE. Parts of the EDF handling are derived from airbreak-plus (MIT).
This server cannot be deployed
Maintenance
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