{"id":"dermatologist-pyomop","name":"pyomop","af_score":58.1,"security_score":41.0,"reliability_score":36.2,"what_it_does":"pyomop is a Python library/CLI for working with OHDSI OMOP CDM (v5.4/v6) databases using SQLAlchemy. It can create/init CDM tables, load OMOP vocabularies, run QueryLibrary queries, execute custom SQL and convert results to pandas DataFrames. It also includes FHIR Bulk Export (NDJSON/NDJSON) import utilities that map FHIR source values to OMOP concepts, and an optional MCP server exposing tools for database operations and query execution. There is also optional LLM-based natural-language query support via langchain extras.","best_when":"You control the database and runtime environment (local/managed instance), and you want a developer-friendly toolkit for OMOP CDM setup, querying, and some ETL (FHIR import), optionally with agent access via MCP.","avoid_when":"You need strong, standardized API authentication/authorization, auditing, and strict operational guardrails for untrusted users—especially for an HTTP-exposed MCP server and for tools that can execute SQL.","last_evaluated":"2026-04-04T19:32:34.697206+00:00","has_mcp":true,"has_api":false,"auth_methods":["Local usage / direct DB credentials via connection parameters or environment variables (PYOMOP_DB/HOST/PORT/USER/PW/SCHEMA).","MCP server via stdio default; HTTP transport available (requires dependencies), but explicit auth mechanisms not described in provided README."],"has_free_tier":false,"known_gotchas":["SQL execution tools can modify databases; agents should use check_sql/validation and constrain scope before run_sql.","create_cdm/create_eunomia limited to local sqlite to avoid inadvertent data loss—agents should respect those constraints to prevent unexpected failures.","HTTP transport is available for MCP but no authentication guidance is provided; avoid exposing publicly without external safeguards.","LLM-based natural language query generation quality depends heavily on prompt/model configuration and may require validation via check_sql before executing."],"error_quality":0.0}