# Technical Context: SkyFi MCP
## Technologies Used
### Core Frameworks
- **ADK (AI Development Kit)**: Integration framework for AI applications
- **LangChain**: Framework for building applications with LLMs
- **AI SDK**: SDK for AI framework integrations
### Communication Protocols
- **HTTP/REST**: Primary communication protocol
- **Server-Sent Events (SSE)**: Real-time updates and notifications
- **WebSockets**: (Optional) For bidirectional communication
### Geospatial Technologies
- **OpenStreetMaps**: Geospatial context and visualization
- **GeoJSON**: Standard format for geospatial data
- **WGS84**: Coordinate reference system
### Data Formats
- **JSON**: Primary data exchange format
- **GeoJSON**: Geospatial data format
- **Markdown**: Documentation format
## Development Setup
### Prerequisites
- Docker and Docker Compose
- Node.js/Python runtime (TBD based on implementation)
- API credentials from SkyFi
- Access to SkyFi Public API documentation
### Local Development
```bash
# Clone repository
git clone <repository-url>
# Setup environment
cp .env.example .env
# Configure API keys and endpoints
# Start services
docker-compose up -d
# Run tests
npm test # or pytest, etc.
```
### Environment Variables
- `SKYFI_API_KEY`: SkyFi API authentication key
- `SKYFI_API_URL`: SkyFi API base URL
- `OPENSTREETMAPS_API_URL`: OpenStreetMaps API endpoint
- `DATABASE_URL`: Database connection string
- `WEBHOOK_SECRET`: Secret for webhook validation
- `LOG_LEVEL`: Logging level (debug, info, warn, error)
## Technical Constraints
### Performance Requirements
- **Response Time**: < 500ms for 95% of API requests
- **Concurrent Connections**: Minimum 100 concurrent connections
- **Throughput**: Handle peak load with graceful degradation
### Security Requirements
- **Encryption**: TLS 1.3 for all communications
- **Authentication**: Secure API key management
- **Compliance**: OWASP Top 10 compliance
- **Audit Logging**: Security event logging
### Scalability Requirements
- **Horizontal Scaling**: Support multiple instances
- **Auto-scaling**: Scale based on load metrics
- **Database**: Connection pooling and read replicas
- **Caching**: Strategy for frequently accessed data
### Reliability Requirements
- **Uptime**: 99.9% SLA
- **Failover**: Automated failover mechanisms
- **Health Checks**: Health check endpoints
- **Monitoring**: Comprehensive monitoring and alerting
## Dependencies
### External Dependencies
- **SkyFi Public API**: Primary data source and service provider
- Availability and stability critical
- API versioning strategy required
- Backward compatibility considerations
- **OpenStreetMaps API**: Geospatial context provider
- Rate limiting considerations
- Caching strategy important
- Fallback mechanisms
- **Major Provider APIs**: Additional geospatial data providers
- Integration complexity varies
- Error handling critical
### Infrastructure Dependencies
- **Cloud Hosting**: For remote deployment option
- Multi-region support preferred
- CDN for documentation and static assets
- **Monitoring Infrastructure**: Logging and metrics
- Application performance monitoring
- Error tracking and alerting
- Usage analytics
### Framework Dependencies
- **ADK**: AI Development Kit integration
- **LangChain**: LangChain framework support
- **AI SDK**: AI SDK framework integration
## API Specifications
### MCP Protocol
- Follows Model Context Protocol specifications
- Stateless HTTP + SSE communication
- RESTful API design principles
### SkyFi API Integration
- Uses SkyFi's public API methods
- Authentication via API keys
- Rate limiting compliance
- Error handling and retries
### OpenStreetMaps Integration
- Geocoding and reverse geocoding
- Map tile access
- Routing information
- Place search
## Data Requirements
### Credential Storage
- **Local**: Secure local credential management
- Encrypted storage
- Environment variable support
- Configuration files
- **Cloud**: Multi-user credential storage
- Encrypted at rest
- Access control
- Audit logging
### Data Formats
- **Input**: JSON, GeoJSON for geospatial data
- **Output**: JSON, standardized response formats
- **Metadata**: Comprehensive metadata for all data products
### Data Retention
- GDPR compliance
- Data retention policies
- User data export capabilities
## Deployment Options
### Local Deployment
- Docker containerization
- Docker Compose for multi-service setup
- Environment-based configuration
- Development and production modes
### Cloud Deployment
- Container orchestration (Kubernetes, ECS, etc.)
- Multi-tenant architecture
- Auto-scaling configuration
- Load balancing
### Hybrid Deployment
- Support for both local and cloud
- Credential management for both
- Seamless switching between modes
## Development Tools
### Code Quality
- Linting and formatting tools
- Type checking (TypeScript/Python type hints)
- Code review process
- Automated testing
### Testing
- Unit tests for business logic
- Integration tests for API endpoints
- End-to-end tests for workflows
- Performance and load testing
### Documentation
- API documentation (OpenAPI/Swagger)
- Code documentation
- Integration guides
- Example code and tutorials
## Monitoring & Observability
### Logging
- Structured logging (JSON format)
- Log levels (debug, info, warn, error)
- Request/response logging
- Error stack traces
### Metrics
- API response times
- Request rates
- Error rates
- Resource utilization
### Alerting
- Error rate thresholds
- Response time degradation
- Resource exhaustion
- Security events
## Security Considerations
### Authentication
- API key rotation support
- OAuth 2.0 for enterprise
- Secure credential storage
- Session management
### Authorization
- Role-based access control
- Resource-level permissions
- Multi-tenant isolation
- Audit trails
### Data Protection
- Encryption in transit (TLS 1.3)
- Encryption at rest
- PII handling compliance
- Data retention policies
### Vulnerability Management
- Regular security audits
- Penetration testing
- Dependency updates
- Security patch management
---
**Last Updated**: January 2025
