Cire — Cosmetic Ingredient Risk Engine
LocalAbout Cire — Cosmetic Ingredient Risk Engine
CIRE is a deterministic API that scores cosmetic ingredient lists in INCI format across five safety-risk categories. It is designed for shopping agents, catalog filtering, compliance workflows, and product recommendation systems.
Key features
- 01Score five ingredient risk categories
- 02Analyze single or batch INCI lists
- 03Evaluate ingredient pair synergy and conflict
- 04Suggest additions based on goals
- 05Return scores with evidence details
Use cases
- 01Filter products for pregnancy and allergen risks
- 02Bulk-scan cosmetic catalog listings
- 03Check ingredients in compliance workflows
- 04Rank products by safety profile
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMECIRE API — Cosmetic Ingredient Risk Engine
Deterministic INCI safety scoring API for AI agents.
Designed for shopping agents, catalog filters, compliance pipelines, and K-beauty recommendation engines.
What is CIRE?
CIRE scores cosmetic ingredient lists (INCI format) for safety risk across 5 categories:
| Category | Description |
|---|---|
irritation_risk | Skin irritation potential |
allergen_risk | Known allergens |
pregnancy_risk | Ingredients unsafe during pregnancy |
acne_risk | Comedogenic ingredients |
interaction_risk | Dangerous ingredient combinations |
Fully deterministic. Rule-based. No ML. Always returns valid JSON.
Quick Start
curl -X POST https://web-production-9cdb4.up.railway.app/v1/analyze \
-H "X-API-Key: YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"inci": "Water, Retinol, Glycolic Acid"}'
Response:
{
"risk_score": 52,
"risk_level": "moderate",
"confidence_score": 65,
"category_results": { ... },
"matches": { ... }
}
risk_score: 0–100 (higher = safer)risk_level:low/moderate/highconfidence_score: evidence strength (0–100)
Authentication
Pass your API key in the X-API-Key header.
X-API-Key: cire-xxxxxxxxxxxx
Get your API key → cire.ai
Pricing
| Plan | Calls | Price |
|---|---|---|
| Starter | 1,000 | $9 |
| Growth | 10,000 | $49 |
| Scale | 100,000 | $299 |
Tier Behavior
- Free tier API key: can call
/v1/analyze,/v1/credits, billing/account endpoints - Pro tier API key: includes Free endpoints +
/v1/synergyand/v1/optimal - Calling Pro endpoints with a Free key returns:
403 Forbidden- clear message:
Pro tier required for this endpoint...
API Reference
Full interactive docs: /docs
Developer entrypoint:
Use-case articles:
POST /v1/analyze
Analyze an INCI string. Costs 1 credit.
POST /v1/batch
Batch analyze up to 100 INCI strings per request. Costs 1 credit per item.
Request:
{ "inci_list": ["Water, Glycerin", "Water, Retinol, Glycolic Acid"] }
POST /v1/synergy (Pro tier)
Deterministic pair scoring for beneficial and risky combinations.
Request:
{ "inci": "Water, Adapalene, Benzoyl Peroxide" }
Response includes:
synergy_scoreconflict_scoreevidence_levelevidence_refs
POST /v1/optimal (Pro tier)
Goal-based deterministic recommendation endpoint.
Request:
{ "inci": "Water, Niacinamide", "goal": "acne" }
Response includes:
recommended_additionsavoid_with_currentevidence_levelevidence_refs
GET /v1/credits
Check remaining credits and key tier.
Billing Automation (Paddle)
/v1/webhookhandlestransaction.completedevents.- When
custom_data.creditsis present, credits are added automatically. - When
custom_data.tierispro/enterprise, API key tier is upgraded automatically. - Pro subscription checkout package ids supported:
pro_monthly,pro_yearly(requires Paddle price IDs in env).
Use Cases
- Shopping agents — filter products by pregnancy safety, allergen risk
- Catalog managers — bulk scan thousands of SKUs
- Compliance pipelines — EU/K-beauty export regulation checks
- Recommendation engines — rank products by safety profile
Tech
- Pure Python, zero ML dependencies
- Deterministic outputs — same input always returns same output
- Evidence-based: EU restriction list, FDA advisories, CIR reports, peer-reviewed consensus
- 13/13 smoke tests passing
Pro Data Enrichment (idempotent)
To enrich Pro formulation tables without duplicating rows:
cd cire-api
python scripts/enrich_pro_seed.py
This script appends missing records for:
evidence_refsingredient_pairsformulation_goals
Built for the AI agent ecosystem. CIRE Certified.
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