Deterministic ingredient analysis: irritation, allergen, pregnancy, acne, interactions. K-beauty compliance ready.
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Need endpoint reference? Open API Docs
Simple REST API + MCP server. Integrates with your favorite AI agents in minutes.
from langchain.tools import tool
import requests
@tool
def analyze_ingredients(inci: str) -> str:
response = requests.post(
"https://web-production-9cdb4.up.railway.app/v1/analyze",
headers={"X-API-Key": "YOUR_API_KEY", "Content-Type": "application/json"},
json={"inci": inci}
)
return response.json()
import anthropic
client = anthropic.Anthropic()
message = client.messages.create(
model="claude-3-opus-20240229",
max_tokens=1024,
tools=[{
"name": "cire_analyze",
"description": "Analyze INCI ingredients",
"input_schema": {"type": "object", "properties": {"inci": {"type": "string"}}}
}],
messages=[{"role": "user", "content": "Analyze: Aqua, Glycerin"}]
)
// In MCP.so agent
const response = await fetch('https://web-production-9cdb4.up.railway.app/v1/analyze', {
method: 'POST',
headers: {
'X-API-Key': 'YOUR_API_KEY',
'Content-Type': 'application/json'
},
body: JSON.stringify({ inci: 'Aqua, Glycerin' })
});
const data = await response.json();
Explore how CIRE works and what you can build with ingredient risk scoring.