HomeCare Cohort MCP
Identifies high-risk patient cohorts and generates care gap closure plans using a synthetic OMOP-like dataset. It provides clinical decision support tools for homecare management through a DuckDB-backed FastMCP server.
README
HomeCare Cohort MCP (Step 1)
FastMCP server that powers the TopGun HomeCare demo Step 1 agents. It exposes tools to surface the high‑risk cohort and produce the Step 1b care gap closure plan from the synthetic OMOP-like dataset.
Prerequisites
- macOS / Linux shell
- Conda (recommended) or Python 3.11
- Repo cloned at
/Users/mdnasir/Documents/proj/TopGun/code/homecare-cohort-mcp
Environment Setup
conda create -n homecare-mcp python=3.11 -y
conda activate homecare-mcp
pip install -r requirements.txt
Build DuckDB Dataset
The synthetic CSVs live in ../synthetic_data. Rebuild the DuckDB file whenever the CSVs change:
cd /Users/mdnasir/Documents/proj/TopGun/code/homecare-cohort-mcp
python -c "from db import ensure_database; ensure_database(force_rebuild=True)"
This creates/overwrites data/homecare.duckdb and materializes helper views (latest_sbp, latest_eye_exam, etc.).
Run the MCP Server Locally
cd /Users/mdnasir/Documents/proj/TopGun/code/homecare-cohort-mcp
uvicorn server:app --reload --port 8010
The Streamable HTTP transport is available at http://127.0.0.1:8010/mcp.
Example Tool Calls
Using the MCP CLI (from the same conda env):
# Identify Step 1a cohort
mcp run server.py:mcp --call get_highrisk_cohort --data '{"limit": 6}'
# Build Step 1b care gap plan
mcp run server.py:mcp \
--call care_gap_closure_plan \
--data '{"patient_ids": ["PAT-00042", "PAT-00058"]}'
Or use MCP Inspector (mcp dev server.py:mcp) to interactively inspect Markdown and structured JSON.
Smoke Test
python smoke_test.py
(Ensures both Step 1 tools execute and return non-empty results.)
Deployment Notes
- Optional build step (if rebuilding DB on deploy):
python -c "from db import ensure_database; ensure_database()" - Configure
MCP_ALLOWED_HOSTS/MCP_ALLOWED_ORIGINSand future API keys (CMS, HDI, Medical Research).
Repository Structure
homecare-cohort-mcp/
├── api/index.py # Vercel entrypoint
├── data/homecare.duckdb # Generated DuckDB file (ignored by default)
├── db.py # DuckDB loader + helper views
├── requirements.txt
├── server.py # FastMCP server with Step 1 tools
├── smoke_test.py # Regression script
└── vercel.json
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