Privacy-first personal intelligence platform combining cloud API for mobile data collection, encrypted single-user AI backend for private analysis, and MCP integration for seamless AI connectivity.
Privacy-first personal intelligence platform combining cloud API, encrypted local backend, and AI connectivity
Production-ready health and productivity data platform with comprehensive endpoints and mobile integration.
Single-user, encrypted personal AI backend for private data management and intelligent assistance.
Model Context Protocol servers for AI integration with standardized tool interfaces.
Native iOS application for health tracking, location monitoring, and data collection.
Production-ready endpoints with automatic documentation and OpenAPI specification
Connect with the Myndy platform using multiple programming languages
# Python SDK Example - Health Data Integration
import requests
from datetime import datetime
class MyndyAPI:
def __init__(self, access_token):
self.base_url = "http://localhost:5000"
self.headers = {
'Authorization': f'Bearer {access_token}',
'Content-Type': 'application/json'
}
def upload_health_data(self, data_type, value, source="manual"):
payload = {
'type': data_type,
'value': value,
'source': source,
'timestamp': datetime.now().isoformat()
}
response = requests.post(
f"{self.base_url}/api/v1/healthdata",
headers=self.headers,
json=payload
)
return response.json()
# Usage
api = MyndyAPI('your_access_token')
result = api.upload_health_data('heart_rate', 75, 'apple_watch')
Multiple ways to interact with the Myndy AI ecosystem
Access your personal dashboard, manage health data, and configure AI settings.
Complete API reference with 142 endpoints, authentication guides, and integration examples.
Connect AI assistants through Model Context Protocol servers for seamless tool access.