PRISM
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@PRISMCheck polysubstance risk for oxycodone and alcohol"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
PRISM — Polysubstance Risk & Interaction Surveillance for Mental-health prescribing
Phase 3 of the PRISM platform.
Clinical decision support checks drug–drug interactions. It largely ignores drug–substance and substance–substance risk — which is where overdose mortality actually comes from (opioid + benzodiazepine, opioid + alcohol).
PRISM is a reasoning layer that closes that gap and grounds an LLM in retrieved evidence rather than recall. It ships as an MCP server with 47 tools and a web platform, both driven by the same validated cascade.
Not a medical device. PRISM surfaces evidence with its provenance. It does not give clinical advice, and the validation harness asserts that it never crosses that line.
The 7-level evidence cascade
Level | Source | Offline? |
1 | Curated interaction knowledge base | yes |
2 | OpenFDA drug labeling | live |
3 | CYP450 / transporter kinetics | yes |
4 | Pharmacodynamic stacking (e.g. CNS depression) | yes |
5 | Drug-class combinations | yes |
6 | FAERS disproportionality signals (Phase 2) | yes |
7 | External interaction sources | live |
Severity is the maximum across levels; confidence scales with the number of independent levels that fire (1 → low, 4+ → very_high). The model cannot invent an interaction — it can only report what a level returned, tagged with that level's source.
On top of the per-pair checks sits compound-risk synthesis: triple CNS-depressant stacks, naloxone candidacy, cocaethylene formation, Beers criteria, teratogenicity — plus automatic screening triggers (AUDIT, DAST-10, CUDIT-R, GAD-7, PHQ-9).
Proxy matching means street terms resolve to pharmacology: heroin → opioid class, street benzos → benzodiazepine class.
Related MCP server: fhir-mcp-suite
Population prior
Phase 1's NSDUH model is imported as a national baseline, so the system can answer "how risky is this patient's profile relative to the population?" rather than only "do these two drugs interact?" — 1,188 risk profiles, 60 annual trend rows, and the logistic coefficients for real-time scoring.
Validation
14 clinical scenarios run end-to-end through the live server and PostgreSQL:
2 cases flagged
life_threatening; 0 instances of overstepping into adviceCase 14 regression (benzodiazepine + opioid) returns
life_threateningacross levels 1, 4, 5, 6, 7 withfda_black_box=True— it returned nothing before the cascade was built, and it is the reason the cascade existsAudit rows persist to
cascade_results,compound_risk_alerts, andscreening_queue
The public repo ships a synthetic 14-case set that reproduces identical severities for
all 14 cases. See scenarios/README.md.
Layout
src/
server.py FastMCP server, 47 registered tools
cascade.py the 7-level engine (DB-optional, unit-testable)
cascade_tools.py DB-backed cascade tools
extra_tools.py remaining registry tools
live_apis.py OpenFDA (L2) + RxNorm (L1) hooks
api/app.py FastAPI bridge for the web UI
db/
schema.sql 24 base tables
migrations_path3.sql +5 cascade tables (29 total)
seed.py curated KB (+ private case loader)
load_scenarios.py scenario loader (synthetic or private)
import_path3_data.py imports Phase 1 + Phase 2 exports
web/ Next.js 14 app (8 pages, Tailwind, Recharts)
scenarios/ synthetic validation cases
validate_scenarios.pySetup
python -m venv venv && ./venv/bin/pip install -r requirements.txt
createdb prism_db
psql prism_db -f src/db/schema.sql
psql prism_db -f src/db/migrations_path3.sql
python -m src.db.seed --reference-only # curated KB, no patient data
python -m src.db.load_scenarios --replace # 14 synthetic cases
python src/db/import_path3_data.py # Phase 1 + Phase 2 exports
python validate_scenarios.pyimport_path3_data.py reads the sibling NSDUH/ and FAERS/ checkouts by default;
override with NSDUH_RESULTS and FAERS_RESULTS environment variables.
Running the server
python -m src.server # stdio (Claude Desktop, Claude Code)
python -m src.server --http # HTTP on :8000Register with an MCP host:
{ "mcpServers": {
"prism": {
"command": "/path/PRISM/venv/bin/python",
"args": ["-m", "src.server"],
"cwd": "/path/PRISM",
"env": { "DATABASE_URL": "postgresql://localhost/prism_db" }
}}}License
MIT (code). Clinical scenario source material is not distributed. Not a medical device; not reviewed by any regulatory authority; must not be used to direct patient care.
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