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Hormonaly-ai

Hormonaly MCP Server

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by Hormonaly-ai

Hormonaly — Public API & Integration Reference

The AI-native infrastructure for peptide, hormone, and longevity medicine.

Status OpenAPI MCP Server Hormonaly-1

This repository is the public-facing integration reference for enterprise partners and API integrators. The MCP server source is published in this repository at Hormonaly-ai/hormonaly-public. For clinical access, visit hormonaly.ai.


Table of Contents

  1. Platform Overview

  2. Architecture Overview

  3. Partner API Reference

  4. MCP Server — Tool Schema

  5. Authentication

  6. Rate Limits & Quotas

  7. Errors & Status Codes

  8. Subscription Tiers

  9. Scribe API

  10. Security & Compliance

  11. Getting Access

  12. Three-Lens Scoring

  13. Webhook Events

  14. API Versioning & Stability

  15. Hormonaly-1 LLM

  16. About Hormonaly

Related MCP server: Medical Calculator MCP Server

Platform Overview

Hormonaly combines three pillars into one platform:

  • Evidence Synthesis — Multi-agent RAG over PubMed + 594 curated protocols with GRADE-style grading (A–D). 6 biomedical databases queried per response: PubMed, ClinicalTrials.gov, Cochrane, Europe PMC, OpenAlex, Semantic Scholar.

  • Clinical Decision Support — Real-time answers, SOAP/DAP/Narrative notes, interaction checks, dosing, and monitoring plans grounded in verified citations.

  • Workflow Tools — The operating layer for clinics, compounding pharmacies, and research teams in the peptide/hormone/longevity space.

By the numbers:

Metric

Value

Protocols

594+ across 31 clinical categories

Studies indexed

10,000+

AI agents

42 specialist + background agents

Design partner clinics

21

Clinicians trained

1,000+

Countries

5

Quality pipeline checks

13 per response

Citation verification

PubMed PMID-validated, 4s timeout

Core products available via API:

Product

Description

Helix

Clinical intelligence engine — multi-agent RAG, GRADE-scored answers, streaming SSE

Scribe

SOAP/DAP/Narrative clinical note generator with citation grounding

PharmacyOS

Compounding-pharmacy intelligence — protocols, interactions, Rx generation

Workspace

Full multi-panel clinical suite — enterprise/partner access

MCP Server

@hormonaly/mcp-server — 24 tools for Claude Desktop and agent frameworks

Architecture Overview

Hormonaly is built on a 42-agent orchestration architecture organized into six categories: Evidence, Research, Clinical, Content, Copilot, and Extraction — plus six continuously-running background agents.

Query Pipeline

Every Helix API call flows through the same deterministic pipeline:

Client query
│
▼
NeMo Guardrails (PII redaction · off-topic filter · nvidia/llama-3.1-nemotron-nano-8b-v1)
│
▼
Agent Router (intent classification → tier selection)
│
├── TIER_1_BEST: Claude Sonnet 4.6 → GPT-4o fallback (complex/clinical queries)
├── TIER_2_BALANCED: Claude Sonnet 4.6 → GPT-4o → Claude Haiku 4.5 fallback (Scribe, CDS, Rx)
└── TIER_3_FAST: Claude Haiku 4.5 → GPT-4o Mini → Gemini 2.5 Flash → Claude Sonnet 4.6 fallback (free tier, Three-Lens scoring)
│
▼
Multi-Database RAG Retrieval (6 databases · 80K token cap)
│
▼
Cross-Encoder Reranker (threshold ≥ 0.35, fallback 0.15)
│
▼
NeMo Parse — Full-text PMC enrichment (top 5 citations)
│
▼
Supervisor/Worker agents (complex multi-compound queries)
│
▼
Quality Gate (13 checks · 70% composite threshold · async)
│
▼
Citation Grounding (PMID verification · 4s timeout per citation)
│
▼
NeMo Output Guardrail (dosing safety scan · inline flags)
│
▼
Streaming SSE response → client

Agent Categories

Category

Agents

Role

Evidence Agent

Primary

Searches 6 biomedical databases, grades findings

Safety Agent

Primary

Screens interactions, contraindications, risk factors

Protocol Agent

Primary

Retrieves compound protocols and monitoring requirements

Contradiction Agent

Primary

Surfaces disagreeing studies, reconciles evidence position

Clinical Decision Agent

Primary

Synthesizes structured clinical recommendation

Quality Gate

Primary

13 automated checks on every response

Background Agents (×6)

Autonomous

Evidence refresh, safety monitoring, knowledge enrichment, protocol audit, stale-check, user-monitor notifications — run continuously

Model Routing

Query Type

Model

Max Tokens

Output

Standard clinical

Claude Sonnet 4.6

4,000

Streaming SSE + evidence grade + citations

Complex (3+ compounds / 30+ words)

Claude Sonnet 4.6

6,000

Streaming SSE + extended synthesis

Evidence mode

Claude Sonnet 4.6

6,000

Deeper literature synthesis

Extended Thinking / Deep Analysis

Claude Sonnet 4.6 (extended)

16,000

SSE + collapsible reasoning panel

Three-Lens Scoring

Claude Haiku 4.5

600

JSON: Longevity / Health / Performance scores + verdict

Multi-agent supervisor/worker

Claude Sonnet 4.6

4,000

SSE + orchestration_steps[]

Scribe / Rx / Pamphlet

Claude Sonnet 4.6

400–4,096

Structured template (SOAP / DAP / Narrative / Rx)

Free-tier (all types)

Claude Haiku 4.5

Same

Same format; shorter context, reduced RAG chunks

Hormonaly-1 (self-hosted)

Hormonaly-1 on NVIDIA NIM

131k ctx

Same SSE format; zero third-party dependency at inference

Model routing note: All tiers use a primary + fallback chain. TIER_1: Claude Sonnet 4.6 → GPT-4o. TIER_2: Claude Sonnet 4.6 → GPT-4o → Claude Haiku 4.5. TIER_3: Claude Haiku 4.5 → GPT-4o Mini → Gemini 2.5 Flash → Claude Sonnet 4.6. NVIDIA NIM (nvidia/llama-3.3-nemotron-super-49b-v1, self-hosted on 8×H100 SXM) is used for citation grounding and the Ask Hormonaly copilot agent. Hormonaly-1 is Hormonaly's proprietary fine-tuned model — deployed on the same H100 infrastructure and progressively integrated to reduce third-party API dependence. See Hormonaly-1 LLM.

Evidence Quality Pipeline

  • Reranker — Cross-encoder scores every RAG chunk ≥ 0.35 (fallback 0.15 for niche compounds)

  • Token cap — 80,000 tokens max RAG context passed to LLM

  • Quality gate — 13 checks across citation validity, answer completeness, clinical coherence, safety flags — composite score ≥ 70% threshold (async, post-hoc)

  • Citation grounding — Every PMID verified against PubMed with 4s timeout; unverified citations are dropped

  • NeMo Parse — Full PMC article text fetched for top 5 citations, structured into intro/methods/results, passed as enriched context

Partner API Reference

Base URL: https://hormonaly.ai/api/v1

Auth: Authorization: Bearer YOUR_API_KEY on every request.

Machine-readable OpenAPI spec: GET /api/v1/helix/openapi.json

All endpoint paths below are relative to the base URL.

Helix Endpoints

POST /helix/query

Submit a clinical question and receive a full Helix response with evidence grade, citations, and clinical verdict.

Request:

{
  "query": "What is the evidence for BPC-157 in tendon repair?",
  "mode": "evidence",
  "stream": true
}

Response (streaming SSE):

data: {"type":"agent_step","step":"classifying intent"}
data: {"type":"agent_step","step":"searching evidence","sources":26}
data: {"type":"agent_step","step":"verifying citations"}
data: {"type":"content","text":"BPC-157 has demonstrated..."}
data: {"type":"metadata","evidence_grade":"C","confidence":62,"verdict":"CONSIDER","citations":5,"sources_consulted":26}
data: {"type":"done"}

Response metadata fields:

Field

Type

Description

evidence_grade

"A"

"B"

confidence

0–100

Composite score from GRADE, citation density, human vs preclinical, inter-source agreement

citations

number

Verified PubMed citations included in response

sources_consulted

number

RAG chunks retrieved from evidence database

agent_type

string

Which specialist agent handled the query

verdict

"ADOPT"

"CONSIDER"

usage

object

Current token usage toward monthly budget

GET /helix/protocols/:compound

Look up evidence-quality-rated protocols for a specific compound.

Example: GET /helix/protocols/bpc-157

Response:

{
  "compound": "bpc-157",
  "evidence_grade": "C",
  "protocols": [
    {
      "indication": "Tendon repair",
      "dose_range": "200–500 mcg/day",
      "route": ["subcutaneous", "intramuscular"],
      "cycle_duration": "4–12 weeks",
      "monitoring": ["liver enzymes at baseline", "symptom review at 4 weeks"]
    }
  ],
  "interactions": [],
  "citations": 5
}

POST /helix/dossier

Generate a comprehensive evidence dossier for a compound (async job). Advanced or Enterprise tier required.

Request:

{ "compound": "semaglutide", "sections": ["mechanism", "efficacy", "safety", "dosing"] }

Response: { "job_id": "dossier_abc123", "status": "queued" }

Poll with GET /helix/dossier/:job_id until status: "complete".

POST /helix/compare

Compare 2–4 protocols head-to-head across evidence grade, safety, dosing, and clinical readiness. Advanced or Enterprise tier required.

Request:

{ "compounds": ["testosterone-cypionate", "testosterone-enanthate"] }

GET /helix/health

Service health check. No authentication required.

{ "status": "ok", "latency_p50_ms": 4200, "citation_coverage": "99%" }

MCP Server — Tool Schema

Package: @hormonaly/mcp-server

The Hormonaly MCP server exposes 24 tools that allow Claude Desktop, Cursor, or any MCP-compatible agent to query the full Helix clinical intelligence stack directly — with no HTTP client code required on your side.

Installation (Claude Desktop)

The MCP server source is available in our GitHub repository. Clone and build locally:

git clone https://github.com/Hormonaly-ai/hormonaly-public.git
cd hormonaly-public/mcp/hormonaly-mcp-server
npm install && npm run build

Then configure Claude Desktop as follows:

// ~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "hormonaly": {
      "command": "node",
      "args": ["/path/to/hormonaly-mcp-server/dist/index.js"],
      "env": {
        "HORMONALY_API_URL": "https://hormonaly.ai",
        "HORMONALY_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Restart Claude Desktop — tools appear immediately.

HTTP/SSE mode (for server-side agents):

HTTP_PORT=3100 node dist/index.js
# SSE: GET http://localhost:3100/sse?sessionId=YOUR_ID
# POST: POST http://localhost:3100/messages?sessionId=YOUR_ID
# Health: GET http://localhost:3100/health

See the mcp/README.md for full setup instructions.

Remote MCP — Claude.ai One-Click Connect

Live · Published May 2026 · Registry: registry.modelcontextprotocol.io

The Hormonaly MCP server is deployed as a remote HTTP/SSE server and listed on the official MCP Registry as io.github.Hormonaly-ai/hormonaly. Enterprise customers using Claude.ai get a one-click Connect experience — no local installation, no Docker, no claude_desktop_config.json edits required.

Property

Value

SSE endpoint

https://mcp.hormonaly.ai/sse

Registry ID

io.github.Hormonaly-ai/hormonaly

Auth header

x-api-key: hk_live_... (Partner API key)

Infrastructure

GCP Cloud Run · Cloudflare DNS · TLS provisioned by GCP

One-Click Connect Flow (Claude.ai Enterprise)

  1. Claude.ai discovers Hormonaly via the MCP Registry — no manual URL entry needed

  2. User clicks Connect — Claude prompts: "Enter your x-api-key"

  3. User pastes their hk_live_... Partner API key (from Partner Portal → API Keys)

  4. All 24 tools activate immediately in the conversation

Authentication & Access Tiers

Tool group

Auth required

Examples

Protocol, Evidence, Compound tools (10 tools)

None — public read access

protocol_search, evidence_search, compound_get_dosing

Helix & agentic tools (7 tools)

API key required

helix_query, run_clinical_workflow, helix_deep_analysis

User tools (4 tools)

Session token

user_get_profile, monitor_protocol_updates

Admin tools (3 tools)

Admin session

admin_get_stats, admin_list_users

Partner API keys start with hk_live_ and are issued from the Partner Portal. The key is passed as the x-api-key SSE header — Claude.ai will prompt for it on first connect.

Full Tool Schema

Helix Tools

Tool

Description

Auth

helix_query

Clinical question → evidence-graded answer with citations and confidence score

API key

helix_compare

Compare 2–4 compounds head-to-head (Advanced/Enterprise)

API key

helix_protocol

Get all protocols for a compound from the Helix API

API key

helix_dossier_start

Start an async dossier generation job (Advanced/Enterprise)

API key

helix_dossier_status

Poll dossier job status by job_id

API key

helix_deep_analysis

Extended analysis with full RAG pipeline, Three-Lens scoring, and PMID citation list

API key

run_clinical_workflow

Full supervisor/worker multi-agent workflow for complex clinical questions

API key

Protocol Tools

Tool

Description

Auth

protocol_search

Search protocol library by compound, category, or condition

Public (no auth)

protocol_get

Get full protocol details by ID or slug

Public (no auth)

protocol_list_categories

List all 31+ protocol categories with counts

Public (no auth)

protocol_get_interactions

Check interactions between a set of compounds

Public (no auth)

Evidence Tools

Tool

Description

Auth

evidence_search

Search PubMed for research on a compound or condition

Public (no auth)

evidence_get

Get full evidence record by ID

Public (no auth)

evidence_grade

Grade a set of PMID references using GRADE framework — returns A/B/C/D per study with rationale

Public (no auth)

Compound Tools

Tool

Description

Auth

compound_search

Search the compound database by name or category

Public (no auth)

compound_get_interactions

Get all known interactions for a compound slug

Public (no auth)

compound_get_dosing

Get evidence-based dosing ranges, routes, and cycle guidance

Public (no auth)

User Tools (session auth required)

Tool

Description

user_get_profile

Get current user's profile

user_get_usage

Get AI usage stats for current user

user_get_saved_protocols

Get protocols saved by current user

monitor_protocol_updates

Check saved protocols for stale evidence (>90 days); returns review_recommended flag

Admin Tools (admin session required)

Tool

Description

admin_get_stats

Get platform-wide statistics

admin_list_users

List users with optional search and pagination

admin_get_ai_costs

Get AI cost breakdown by model and endpoint

Agentic Workflow Tools

Three tools activate the full multi-agent pipeline:

run_clinical_workflow — Supervisor/worker pattern. Decomposes complex clinical questions into 3–4 parallel sub-tasks (evidence search, interaction check, protocol lookup, clinical synthesis), dispatches specialist agents, and returns a synthesized report with orchestration_steps[] showing each agent's task, result, timing, and confidence. Latency: 30–90 seconds for complex queries.

helix_deep_analysis — Extended deep analysis using the full RAG pipeline. Returns Three-Lens scoring across three independent clinical lenses (Longevity / Health & Disease / Performance), full PMID citation list, confidence breakdown by section, and overall evidence grade (A–D).

monitor_protocol_updates — Checks saved protocols against a 90-day staleness threshold. Returns a review_recommended flag and last evidence update date per protocol. Use weekly/monthly to stay current with the literature.

MCP Tool Input Schemas

All 24 tool schemas. The inputSchema block is what Claude Desktop and MCP clients use to validate parameters before sending.

helix_query

{
  "name": "helix_query",
  "inputSchema": {
    "type": "object",
    "properties": {
      "question": { "type": "string", "description": "Clinical question", "maxLength": 10000 },
      "language": { "type": "string", "enum": ["en","ar"], "default": "en" },
      "detail_level": { "type": "string", "enum": ["clinical","summary"], "default": "clinical" },
      "include_citations":{ "type": "boolean", "default": true },
      "include_three_lens":{ "type": "boolean", "default": false },
      "api_key": { "type": "string", "description": "Override env API key" }
    },
    "required": ["question"]
  }
}

helix_compare (Advanced/Enterprise)

{
  "name": "helix_compare",
  "inputSchema": {
    "type": "object",
    "properties": {
      "compounds": { "type": "array", "items": { "type": "string" }, "minItems": 2, "maxItems": 4 },
      "indication": { "type": "string", "default": "General comparison" },
      "language": { "type": "string", "enum": ["en","ar"], "default": "en" },
      "api_key": { "type": "string" }
    },
    "required": ["compounds"]
  }
}

helix_protocol

{
  "name": "helix_protocol",
  "inputSchema": {
    "type": "object",
    "properties": {
      "compound": { "type": "string", "maxLength": 200 },
      "language": { "type": "string", "enum": ["en","ar"], "default": "en" },
      "api_key": { "type": "string" }
    },
    "required": ["compound"]
  }
}

helix_dossier_start (Advanced/Enterprise)

{
  "name": "helix_dossier_start",
  "inputSchema": {
    "type": "object",
    "properties": {
      "compound": { "type": "string", "maxLength": 500 },
      "language": { "type": "string", "enum": ["en","ar"], "default": "en" },
      "api_key": { "type": "string" }
    },
    "required": ["compound"]
  }
}

helix_dossier_status

{
  "name": "helix_dossier_status",
  "inputSchema": {
    "type": "object",
    "properties": {
      "job_id": { "type": "string" },
      "api_key": { "type": "string" }
    },
    "required": ["job_id"]
  }
}

helix_deep_analysis (Enterprise)

{
  "name": "helix_deep_analysis",
  "inputSchema": {
    "type": "object",
    "properties": {
      "topic": { "type": "string", "description": "Clinical topic for deep analysis", "maxLength": 10000 },
      "language": { "type": "string", "enum": ["en","ar"], "default": "en" },
      "api_key": { "type": "string" }
    },
    "required": ["topic"]
  }
}

run_clinical_workflow

{
  "name": "run_clinical_workflow",
  "inputSchema": {
    "type": "object",
    "properties": {
      "question": { "type": "string", "description": "Complex clinical question", "maxLength": 10000 },
      "patient_context": { "type": "string", "description": "Optional: age, sex, conditions, medications" },
      "language": { "type": "string", "enum": ["en","ar"], "default": "en" },
      "api_key": { "type": "string" }
    },
    "required": ["question"]
  }
}

monitor_protocol_updates (session auth)

{
  "name": "monitor_protocol_updates",
  "inputSchema": {
    "type": "object",
    "properties": {
      "session_token": { "type": "string" },
      "compound_filter": { "type": "array", "items": { "type": "string" }, "description": "Filter to specific compounds" }
    }
  }
}
{
  "name": "protocol_search",
  "inputSchema": {
    "type": "object",
    "properties": {
      "query": { "type": "string" },
      "category": { "type": "string", "description": "e.g. 'weight-loss', 'hormones'" },
      "limit": { "type": "number", "default": 10 }
    },
    "required": ["query"]
  }
}

protocol_get

{
  "name": "protocol_get",
  "inputSchema": {
    "type": "object",
    "properties": { "id": { "type": "string" } },
    "required": ["id"]
  }
}

protocol_list_categories

{
  "name": "protocol_list_categories",
  "inputSchema": { "type": "object", "properties": {} }
}

protocol_get_interactions

{
  "name": "protocol_get_interactions",
  "inputSchema": {
    "type": "object",
    "properties": {
      "compounds": { "type": "array", "items": { "type": "string" }, "minItems": 2,
      "description": "Compound slugs to screen" }
    },
    "required": ["compounds"]
  }
}
{
  "name": "evidence_search",
  "inputSchema": {
    "type": "object",
    "properties": {
      "compound": { "type": "string" },
      "max_results": { "type": "number", "default": 10 }
    },
    "required": ["compound"]
  }
}

evidence_get

{
  "name": "evidence_get",
  "inputSchema": {
    "type": "object",
    "properties": { "id": { "type": "string" } },
    "required": ["id"]
  }
}

evidence_grade

{
  "name": "evidence_grade",
  "inputSchema": {
    "type": "object",
    "properties": {
      "ids": { "type": "array", "items": { "type": "string" }, "minItems": 1, "maxItems": 20,
      "description": "Evidence record IDs to GRADE-score" }
    },
    "required": ["ids"]
  }
}
{
  "name": "compound_search",
  "inputSchema": {
    "type": "object",
    "properties": {
      "query": { "type": "string" },
      "category": { "type": "string" }
    },
    "required": ["query"]
  }
}

compound_get_interactions

{
  "name": "compound_get_interactions",
  "inputSchema": {
    "type": "object",
    "properties": { "slug": { "type": "string", "description": "e.g. 'semaglutide'" } },
    "required": ["slug"]
  }
}

compound_get_dosing

{
  "name": "compound_get_dosing",
  "inputSchema": {
    "type": "object",
    "properties": { "slug": { "type": "string", "description": "e.g. 'testosterone-cypionate'" } },
    "required": ["slug"]
  }
}

user_get_profile

{
  "name": "user_get_profile",
  "inputSchema": {
    "type": "object",
    "properties": { "session_token": { "type": "string" } }
  }
}

user_get_usage

{
  "name": "user_get_usage",
  "inputSchema": {
    "type": "object",
    "properties": { "session_token": { "type": "string" } }
  }
}

user_get_saved_protocols

{
  "name": "user_get_saved_protocols",
  "inputSchema": {
    "type": "object",
    "properties": { "session_token": { "type": "string" } }
  }
}

admin_get_stats

{
  "name": "admin_get_stats",
  "inputSchema": {
    "type": "object",
    "properties": { "admin_session_token": { "type": "string" } }
  }
}

admin_list_users

{
  "name": "admin_list_users",
  "inputSchema": {
    "type": "object",
    "properties": {
      "limit": { "type": "number", "default": 20 },
      "offset": { "type": "number", "default": 0 },
      "search": { "type": "string" },
      "admin_session_token": { "type": "string" }
    }
  }
}

admin_get_ai_costs

{
  "name": "admin_get_ai_costs",
  "inputSchema": {
    "type": "object",
    "properties": {
      "days": { "type": "number", "default": 30 },
      "admin_session_token": { "type": "string" }
    }
  }
}

Authentication

Hormonaly uses two independent auth systems — do not mix them:

1. Helix Data API — Bearer Token

All /api/v1/* endpoints require: Authorization: Bearer YOUR_API_KEY

API keys are SHA-256 hashed before storage. The plaintext key is shown exactly once at creation — store it immediately in your secrets manager. If lost, revoke and rotate; there is no recovery path. REST /api/v1/* endpoints expect the key in the Authorization: Bearer header; the remote MCP/SSE server expects it in the x-api-key: hk_live_... header.

Key management: Partner Portal → API Keys (/partner/api)

2. Partner Portal — Session Auth

The Partner Portal (/partner/*) uses session-based authentication. Log in at /partner/login with email + password. This session does not grant access to the data API.

Key Lifecycle

  1. Create — Full key shown ONCE in modal; copy immediately.

  2. Multiple active keys — Creating a new key does NOT revoke existing keys.

  3. Revoke — Instant. Any request using that key returns 401 immediately.

  4. Lost key — Revoke and create a new key. No plaintext recovery.

Rate Limits & Quotas

Plan

Monthly Base

Tokens Included

Rate Limit

Overage Rate

Hard Cap

API Starter

$499

5M tokens

60 req/min

$100 / 1M

10M tokens (then 429)

API Advanced

$1,999

25M tokens

150 req/min

$80 / 1M

75M tokens (then 429)

API Enterprise

$4,999

75M tokens

Custom

$25 / 1M

None (overage billed)

Legacy partners (pre-billing)

20 req/min

Over-limit response: HTTP 429 with Retry-After header. Burst behavior: sliding 60-second window, no burst allowance.

Response Latency

Endpoint

P50 latency

POST /api/v1/helix/query

3–12 seconds

POST /api/v1/scribe/generate

15–45 seconds

GET /api/v1/helix/protocols/:compound

< 200ms

run_clinical_workflow (MCP)

30–90 seconds

usage Object

Every POST /api/v1/helix/query response includes a top-level usage object reflecting real-time token consumption:

{
  "usage": {
    "tokensUsedThisMonth": 1234567,
    "monthlyTokenBudget": 5000000,
    "percentUsed": 24.7,
    "hardCapTokens": 10000000,
    "hardCapExceeded": false,
    "quotaThresholdsCrossed": [80]
  }
}

Errors & Status Codes

{
  "error": {
    "code": "RATE_LIMITED",
    "message": "Request rate exceeded. Retry after 23s.",
    "request_id": "req_01HXYZ..."
  }
}

Status

error.code

Meaning

Recommended client behavior

400

INVALID_REQUEST

Malformed JSON or missing required field

Fix the request; do not retry as-is

401

MISSING_AUTH

No Authorization header

Attach Authorization: Bearer YOUR_API_KEY

401

INVALID_KEY

Key not recognized or revoked

Rotate the key via Partner Portal

403

TIER_REQUIRED

Endpoint requires Advanced or Enterprise tier

Upgrade plan

404

NOT_FOUND

Compound, protocol, or job ID does not exist

Verify identifier

422

VALIDATION_FAILED

Semantic validation failed

Inspect error.message

429

RATE_LIMITED

Per-minute request rate exceeded

Honor the Retry-After header

429

BUDGET_EXCEEDED

Pre-call budget cap exceeded

Wait for budget window or contact billing

5xx

INTERNAL_ERROR

Unexpected server error

Retry with exponential backoff (max 3 attempts)

503

UPSTREAM_TIMEOUT

A biomedical database or model upstream timed out

Retry after 5–10s

Subscription Tiers

API Starter

API Advanced

API Enterprise

Monthly base

$499

$1,999

$4,999

Tokens included / month

5,000,000

25,000,000

75,000,000

Overage rate

$100 / 1M tokens

$80 / 1M tokens

$25 / 1M tokens

Hard cap

10M tokens — then 429

75M tokens — then 429

None (overage billed)

Rate limit

60 req/min

150 req/min

Custom

Feature

API Starter

API Advanced

API Enterprise

/api/v1/helix/query

Yes

Yes

Yes

/api/v1/scribe/generate

Yes

Yes

Yes

/api/v1/helix/dossier

No — 403

Yes

Yes

/api/v1/helix/compare

No — 403

Yes

Yes

White-label portal

No

No

Yes

BAA (HIPAA)

No

No

Yes

Dedicated support

No

No

Yes

Scribe API

Mounted at /api/v1/scribe. Available on all plans.

POST /scribe/generate

{
  "note_format": "soap",
  "patient_context": {
    "age": 45, "sex": "male",
    "diagnoses": ["hypogonadism"],
    "active_protocols": ["testosterone-cypionate"],
    "lab_values": { "total_testosterone": "250 ng/dL", "LH": "1.2 mIU/mL" }
  },
  "visit_notes": "Patient presents for quarterly follow-up."
}

Supported note_format: soap | dap | narrative (default: soap). Response includes note, interaction_alerts, monitoring_plan, confidence_score, evidence_grade. Latency: 15–45 seconds.

GET /scribe/health

No authentication required.

Security & Compliance

Security Controls

Control

Implementation

API key storage

SHA-256 hash only — plaintext never stored

Rate limiting

Atomic SQL counter (sliding 60s window, cross-instance safe)

Budget enforcement

Pre-call check; 429 before any LLM tokens consumed

Session fixation

regenerate() on every login

IDOR protection

All dossiers and engagement records are ownership-checked

Mass assignment

Clean — all inputs validated

Search injection

All ILIKE/tsquery parameterized via Drizzle ORM

Webhook security

HMAC-SHA256 signature verification (Stripe + Resend); idempotency on all events

Path traversal

Boundary whitelist on all file-serving endpoints

Auth rate limiting

All auth endpoints independently rate-limited (PG-backed, cross-instance)

TLS

TLS 1.3 in transit; AES-256 at rest

WAF

Cloud Armor active; scanner traffic blocked

CSP / HSTS / CORS

All headers configured; report-uri Sentry telemetry active

Clinical guardrails

NVIDIA NeMo · nvidia/llama-3.1-nemotron-nano-8b-v1 (input PII redaction + off-topic filter) · nvidia/llama-3.3-nemotron-super-49b-v1 (citation grounding + dosing safety scan)

Supply chain

private: true in package.json; dependency audit clean (Mar 2026)

Compliance Posture

  • HIPAA-aligned architecture — No PHI stored by default; patient data is session-scoped unless the Clients feature is explicitly enabled.

  • BAA available — Enterprise customers receive a Business Associate Agreement.

  • Encryption — TLS 1.3 in transit, AES-256 at rest, geographically redundant encrypted backups.

  • Audit logging — All auth events, API key usage, AI calls, and admin actions written to a tamper-evident audit log.

  • Data residency — GCC-region and EU residency available on request.

  • Infrastructure — GCP (us-central1), Cloud Run (autoscaling), Cloud SQL PostgreSQL + pgvector.

GCP inherits: SOC 2 Type II, ISO 27001, HIPAA, PCI DSS, 150+ compliance certifications at the infrastructure layer.

AI Safety

  • NVIDIA NeMo safety layer on every query: input PII redaction + off-topic/harm-framing filter (nvidia/llama-3.1-nemotron-nano-8b-v1, self-hosted on H100); output dosing safety scan with inline warnings.

  • PEPTIDE_SAFETY_FOOTER and HELIX_REGULATORY_RULES active on all responses.

  • No model training on user data — query data is not used to train or fine-tune any third-party model. Production interactions are quality-filtered and used exclusively in the Hormonaly-1 Data Flywheel (see Hormonaly-1 LLM).

Internal benchmarks (May 2026):

Dimension

Score

Citation-grounding pass rate

100%

Safety block rate (on flagged inputs)

96%

RAG retrieval pass rate

99%

Citation faithfulness (PMID-verified)

97%

Uptime

  • Target SLA — 99.9% monthly uptime for all production API endpoints.

  • P1 incidents — Acknowledged within 15 minutes, resolved within 4 hours.

  • Status — status.hormonaly.ai

  • Maintenance — Announced ≥ 72 hours in advance.

Getting Access

1. Request Partner API Access

Contact the Hormonaly team to request a Partner API account:

  • Email: info@hormonaly.ai

  • Enterprise / BD: hormonaly.ai/about

  • Plans: hormonaly.ai/pricing

You will receive your API key and a cURL quickstart example by email, plus a separate Partner Portal invitation to set up your dashboard at /partner/dashboard.

2. Request Hormonaly-1 LLM Licensing

For enterprise integrators interested in licensing Hormonaly-1 for white-label or embedded clinical AI deployments:

See the Hormonaly-1 LLM section for full model details and licensing tiers.

3. First API Call

curl -X POST https://hormonaly.ai/api/v1/helix/query \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query": "What is the evidence for semaglutide in metabolic optimization?", "stream": false}'

4. OpenAPI Spec

curl https://hormonaly.ai/api/v1/helix/openapi.json

5. Full Documentation

Resource

URL

API Reference

hormonaly.ai/api-docs

Technical Manual

hormonaly.ai/manual

Partner Portal

hormonaly.ai/partner/login

Integration Guide

hormonaly.ai/integration-guide

Platform

hormonaly.ai

About / Leadership

hormonaly.ai/about

Status

status.hormonaly.ai

Three-Lens Scoring

Three-Lens is Hormonaly's proprietary multi-domain evidence scoring framework. It evaluates a compound independently through three clinical lenses, producing per-lens efficacy and safety scores, an evidence level (A–E), and a synthesized overall recommendation.

Lenses

Lens

Domain Label

Focus

Key Endpoints

longevity

Longevity & Anti-Ageing

Slow or reverse biological ageing to extend healthspan and lifespan

Epigenetic clock deceleration, telomere dynamics, senescent cell clearance, NAD+ levels, mitochondrial function, autophagy markers

health_disease

Health & Disease Prevention

Detect, prevent, or reverse chronic disease

CVD risk reduction, HbA1c, inflammatory markers (CRP, IL-6), blood pressure, lipid profile, insulin sensitivity

performance

Performance Optimization

Elevate cognitive, metabolic, and physical function above baseline

VO2max, grip strength, cognitive processing speed, sleep quality, body composition, HRV, exercise recovery

Score Structure

Each lens returns a DomainScore object:

{
  "domain": "longevity",
  "domainLabel": "Longevity & Anti-Ageing",
  "efficacyScore": 7.4,
  "safetyScore": 8.1,
  "evidenceLevel": "C",
  "evidenceLevelLabel": "Low",
  "studyCount": 12,
  "bestStudyType": "Randomized Controlled Trial",
  "keyFindings": ["Demonstrated mTOR inhibition in human pilot (n=24)"],
  "limitations": ["Most trials are short-duration (<12 weeks)"],
  "relevantEndpoints": ["HbA1c", "fasting insulin", "body weight"]
}

Evidence Levels (5-tier)

Level

Label

Description

A

High

Multiple consistent RCTs or meta-analyses

B

Moderate

At least one RCT or multiple cohort studies

C

Low

Case series, observational studies

D

Very Low

Expert opinion / anecdotal

E

Preclinical

Animal or in vitro studies only

Overall Recommendations

Verdict

Meaning

ADOPT

Strong, consistent human evidence supports use

CONSIDER

Reasonable evidence — use with informed consent and monitoring

WATCH_AND_WAIT

Promising signals but insufficient evidence for routine use

AVOID

Evidence against use or unacceptable safety risk

INSUFFICIENT_DATA

Too little data to score meaningfully

Requesting Three-Lens Scores

Three-Lens is returned in helix_query when include_three_lens: true, and always in helix_deep_analysis and run_clinical_workflow:

curl -X POST https://hormonaly.ai/api/v1/helix/query \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query": "What is the evidence for rapamycin in longevity?", "include_three_lens": true}'

Webhook Events

Hormonaly delivers async job results (dossiers, batch operations) to partner-configured webhook URLs. Configure in the Partner Portal under Settings → Webhooks.

Event Types

Event

Trigger

Payload Fields

job.completed

Async job finishes successfully

job_id, type, status: "completed", result, completed_at

job.failed

Async job fails after all retries

job_id, type, status: "failed", error, completed_at

Signature Verification

Every delivery is signed with HMAC-SHA256. The signature is in the X-Hormonaly-Signature header:

X-Hormonaly-Signature: sha256=<hex_digest>
const crypto = require('crypto');
function verifyWebhook(secret, rawBody, receivedSig) {
  const expected = 'sha256=' + crypto
    .createHmac('sha256', secret)
    .update(rawBody, 'utf8')
    .digest('hex');
  return crypto.timingSafeEqual(Buffer.from(expected), Buffer.from(receivedSig));
}

Delivery policy: 3 attempts maximum, exponential back-off (1s → 8s → 64s), 10s timeout per attempt, HTTP 2xx = delivered.

API Versioning & Stability

Current version: /api/v1/

Tier

Indicator

Commitment

Stable

No label

Breaking changes announced ≥ 90 days in advance; old version supported ≥ 6 months after deprecation

Beta

(beta) in docs

Interface may change; best-effort stability

Deprecated

(deprecated) in docs

Scheduled for removal; migration path documented

Changelog

Date

Change

Jun 2026

Hormonaly-1 LLM launched — proprietary clinical LLM live on NVIDIA H100 infrastructure; full model card, licensing path, and API integration notes added to public docs

Jun 2026

Overage rate corrected: Starter $100/1M, Advanced $80/1M, Enterprise $25/1M; design partners updated to 21; Hormonaly Library added

Jun 2026

Status emoji replaced with text labels for a cleaner format; Anabol.ai consumer harm-reduction platform added

Jun 2026

Added investors & strategic partners: KBW Ventures (portfolio company) and NVIDIA Inception / Innovation Lab grant

Jun 2026

NVIDIA models updated: NeMo guardrails upgraded to nvidia/llama-3.1-nemotron-nano-8b-v1; NIM inference model nvidia/llama-3.3-nemotron-super-49b-v1 documented

Jun 2026

Tier fallback chains corrected in Query Pipeline and Model Routing: TIER_2 now shows 3-deep chain; TIER_3 now shows 4-deep chain

May 2026

Background agents count updated to ×6; Model routing updated; Tiered token budgets documented; Full 24-tool MCP schemas published; Three-Lens Scoring, Webhook Events, API Versioning sections added

Hormonaly-1 LLM

Live · June 2026 · NVIDIA Innovation Lab Grant · NIM Stack · H100 · Nemotron 49B · Arabic & English

Hormonaly-1 is Hormonaly's proprietary clinical large language model — engineered specifically for peptide, hormone, and metabolic medicine. It is fully trained, merged, and deployed on Hormonaly's own NVIDIA H100 infrastructure via the NVIDIA NIM inference stack, with zero dependency on third-party AI APIs at inference time.

Overview

Property

Value

Model name

Hormonaly-1

Base model

nvidia/llama-3.3-nemotron-super-49b-v1 (Nemotron Super 49B)

Training method

Supervised Fine-Tuning (SFT) with LoRA — clinical platform interactions, quality-filtered

Domain

Peptide, hormone, and metabolic medicine

Languages

Arabic (عربي) + English — natively bilingual

Context window

131,072 tokens

Throughput

~65 tokens/second

Inference stack

NVIDIA NIM (self-hosted)

Hardware

8× NVIDIA H100 SXM GPUs

Status

Live — June 2026

Backing

NVIDIA Inception member + NVIDIA Innovation Lab grant recipient

Capabilities

Clinical Reasoning at Scale — Trained directly on real clinical platform interactions via SFT with LoRA. Understands clinical nuance, contraindications, and dosing context across 594+ protocols and 10,000+ indexed studies.

Bilingual: Arabic & English — The first clinical LLM optimized for both MENA and English-speaking healthcare markets simultaneously. Both languages are first-class citizens in training data and inference.

NVIDIA NIM Stack — Built on the NVIDIA NIM inference stack with Nemotron Super 49B deployed on 8×H100 SXM GPUs. 131k token context window at 65 tok/s for real-time clinical workflows.

Evidence-Graded Safety — Every response inherits the Helix evidence-grading pipeline: GRADE-style scoring (A–D), PMID-verified citations, and NeMo safety guardrails. Hormonaly-1 does not hallucinate citations — unverified PMIDs are dropped before delivery.

Zero Third-Party Dependency at Inference — Real platform interactions are continuously logged and quality-filtered via the Data Flywheel pipeline, reducing dependence on third-party LLM APIs over time.

Data Flywheel & Training Pipeline

Hormonaly-1 is produced by the Data Flywheel pipeline — a continuous improvement loop running on the same H100 infrastructure:

  1. Production interactions from the Helix API and MCP server are logged and quality-filtered (citation faithfulness, clinical coherence, safety flag review).

  2. NeMo SFT fine-tuning is run on H100 GPUs 4–7 (LoRA, base: nvidia/llama-3.3-nemotron-super-49b-v1).

  3. Merged model checkpoints are validated against internal clinical benchmarks before promotion to inference.

  4. NVIDIA NIM serves the merged model on GPUs 0–3 for production inference.

This pipeline is funded in part by the NVIDIA Innovation Lab grant and supported by NVIDIA Inception membership.

API Integration

Hormonaly-1 is served through the same Helix API endpoints — no schema changes required for integrators. When Hormonaly-1 is active in the routing chain, responses carry an additional model field in the metadata:

{
  "type": "metadata",
  "evidence_grade": "B",
  "confidence": 78,
  "verdict": "CONSIDER",
  "citations": 7,
  "model": "hormonaly-1",
  "inference_provider": "nvidia-nim-self-hosted"
}

The inference_provider: "nvidia-nim-self-hosted" field distinguishes Hormonaly-1 responses from third-party model responses.

Licensing

Hormonaly-1 is available for enterprise licensing for white-label or embedded clinical AI deployments. Licensing tiers cover:

  • API access — Hormonaly-1 via the Helix API with full evidence pipeline

  • Embedded deployment — Self-hosted Hormonaly-1 within a partner's own NVIDIA infrastructure

  • White-label — Hormonaly-1 branded under your clinical product

To request licensing:

  • Email: partnerships@hormonaly.ai (subject: Hormonaly-1 Licensing Inquiry)

  • Web: hormonaly.ai/hormonaly-llm

  • Response within 1 business day.

Model Card Summary

Dimension

Details

Intended use

Clinical decision support, protocol lookup, evidence synthesis, note generation for licensed healthcare providers

Not intended for

Consumer self-diagnosis, emergency medical guidance, replacing licensed clinical judgment

Training data

Quality-filtered clinical platform interactions (Helix API, MCP), augmented with curated clinical literature

Safety measures

NVIDIA NeMo guardrails (PII redaction, dosing safety scan), PEPTIDE_SAFETY_FOOTER, HELIX_REGULATORY_RULES

Output disclaimer

Medical disclaimer included on every response; output augments — does not replace — licensed clinician judgment

Data privacy

No PHI stored; session-scoped; training data de-identified and quality-reviewed

About Hormonaly

Hormonaly was founded by Fady Hannah-Shmouni, MD FRCPC — board-certified endocrinologist and geneticist, NIH-trained, Professor at UBC, with 100+ peer-reviewed publications (h-index 27) and two international clinical guidelines co-authored.

Leadership: Fady Hannah-Shmouni, MD FRCPC (CEO/CBO/Founder) · Omar Saleem, MD (Director, AI Academy) · Matt D. Kramer (Healthcare Technology Strategist)

Advisory Board: Ali Mostashari, PhD (LifeNome) · Constantine Stratakis, MD (ASTREA) · Cory S. Goldberg, MD · John Kozman (Supernatural) · Dominik Thor, MSc (GCLS) · Labib Ghulmiyyah, MD · Zahraa Abdul Sater, MBBS

Backed by: Hormonaly is a portfolio company of KBW Ventures, the global investment firm founded by Prince Khaled bin Alwaleed bin Talal. Hormonaly is also an NVIDIA Inception member and a recipient of an NVIDIA Innovation Lab grant — accelerated compute and engineering support to build clinical-grade, domain-specific AI models for peptide and hormone medicine. In production: a self-hosted 8×H100 SXM node runs three NVIDIA NIM microservices — nvidia/llama-3.3-nemotron-super-49b-v1 (LLM inference for citation grounding and the Ask Hormonaly copilot), nvidia/llama-3.1-nemotron-nano-8b-v1 (NeMo guardrails: PII redaction + dosing safety), and a Rerank NIM — plus the Hormonaly-1 Data Flywheel pipeline that fine-tunes Hormonaly-1 using NeMo SFT on H100 GPUs 4–7 (base: nvidia/llama-3.3-nemotron-super-49b-v1, LoRA fine-tuning on high-quality production interactions), progressively reducing dependence on third-party APIs over time.

Design partner clinics & partners (21): FORM Face + Body, REBORNE Longevity, Healthspan Digital, PearlMD, Toronto Functional Medicine Centre, A-Life, Astrea Health, Valeo Health, Celia Holdings, Celia Rx, Pillvery, and others.

Educational partners: DrVibe.ai (1,000+ clinicians trained across 5 countries) · GCLS.ai (Geneva College of Longevity Science).

Hormonaly Library (hormonaly.com): Evidence-based hormone-health books and downloadable PDF guides authored by Fady Hannah-Shmouni, MD FRCPC — including The Peptide Pocket Guide, Peptides Simplified, BPC-157: Evidence Simplified, Peptides, Hormones & Longevity, and Aesthetic & Regenerative Endocrinology (with Arabic editions and free samples).

Anabol.ai (anabol.ai): A free, consumer-facing harm-reduction and education platform powered by Hormonaly. AI-powered, evidence-graded research across steroids, peptides, SARMs, and regenerative compounds. Educational resource only — not medical advice.

Enterprise — TelehealthOS & Canvas Medical: For enterprise care teams, Hormonaly offers TelehealthOS — a custom, AI-native infrastructure for launching and scaling peptide, hormone, skincare, and longevity telehealth operations. Through a partnership with Canvas Medical, enterprise customers get HIPAA, SOC 2, and HITRUST certified clinical infrastructure: EPCS-ready certified e-prescribing, an integrated EHR/EMR, and compounding fulfillment through 503A and 503B FDA-registered, cGMP pharmacies. Contact info@hormonaly.ai or see hormonaly.ai/telehealth-os.


Hormonaly is an educational and clinical decision-support platform. All AI output is intended to augment — not replace — the clinical judgment of a licensed healthcare professional. A medical disclaimer is included on every response. For security disclosures, email fady@hormonaly.ai or use GitHub private vulnerability reporting.

This repository contains no proprietary source code. © Hormonaly — All rights reserved.

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