hormonaly-ai/hormonaly-public — explained in plain English
Analysis updated 2026-05-18
Search PubMed, ClinicalTrials.gov, and other databases for graded evidence on a clinical question.
Generate SOAP, DAP, or Narrative clinical notes with citations attached.
Check for drug or compound interactions before finalizing a treatment plan.
Connect an AI assistant like Claude Desktop to Hormonaly's data via its MCP server.
| hormonaly-ai/hormonaly-public | 0verflowme/alarm-clock | 0xhassaan/nn-from-scratch | |
|---|---|---|---|
| Stars | 0 | — | 0 |
| Language | — | CSS | Python |
| Last pushed | — | 2022-10-03 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | hard | easy | moderate |
| Complexity | 4/5 | 2/5 | 4/5 |
| Audience | ops devops | vibe coder | developer |
Figures from each repo's GitHub metadata at analysis time.
This is a documentation-only repo, integration requires an enterprise API key and Hormonaly platform access.
Hormonaly is a clinical software platform designed for medical professionals working in peptide, hormone, and longevity medicine: areas that cover treatments like hormone optimization, peptide therapies, and anti-aging protocols. This public repository contains no source code, it is the integration reference for enterprise partners and API developers who want to connect their own systems to the Hormonaly platform. The platform combines three capabilities. First, evidence synthesis: it searches six biomedical databases (including PubMed, ClinicalTrials.gov, and Cochrane) and applies GRADE-style grading (A through D) to score how strong the evidence is for a given clinical question. Second, clinical decision support: it generates structured clinical notes in standard formats (SOAP, DAP, Narrative), checks drug interactions, and produces dosing and monitoring plans anchored to verified citations. Third, workflow tools: it provides a full operating layer for clinics, compounding pharmacies, and research teams. The underlying architecture uses over 40 AI agents organized into categories: evidence retrieval, safety screening, protocol lookup, contradiction detection, and quality checking, with every query passing through a 13-step quality gate. Responses stream in real time via SSE (Server-Sent Events), and all cited PubMed IDs are verified against PubMed before being included. The integration surface documented here includes a REST API, an MCP server (a protocol for connecting AI assistants like Claude Desktop to external tools), webhook events, and authentication via API key. The full README is longer than what was provided.
A clinical decision support and evidence-search platform for hormone and peptide medicine, with a public API and MCP server for integrators.
No license information is provided in this integration reference repository.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly ops devops.
This repo across BitVibe Labs
Verify against the repo before relying on details.