# Hype Dash
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[](https://modelcontextprotocol.io)
Production-ready TypeScript SDK for creating and managing Lark/Feishu dashboards via REST API with Model Context Protocol (MCP) server support.
## Features
- **Type-Safe**: Full TypeScript support with comprehensive type definitions
- **Fluent API**: Intuitive builder pattern for creating dashboard blocks
- **7 Block Types**: Charts, Metrics, Views, Text, Lists, Tab Pages, and Filters
- **MCP Server**: Native Claude Code integration via Model Context Protocol
- **Production Ready**: Error handling, retries, logging, and validation
- **Batch Operations**: Efficiently create multiple blocks at once
- **2025 Dashboard Features**: Latest Lark dashboard capabilities
- **Python SDK**: Comprehensive Python SDK for Lark Base data management
## Installation
### TypeScript/JavaScript
```bash
npm install @hypelab/hype-dash
```
### Python
```bash
cd python
pip install -r requirements.txt
```
See [Python SDK Documentation](python/README.md) for detailed setup and usage.
## Quick Start
### Basic Usage
```typescript
import { LarkDashboardClient, ChartBlockBuilder, AggregationType } from '@hypelab/hype-dash';
const client = new LarkDashboardClient({
apiKey: process.env.LARK_API_KEY!,
region: 'sg', // 'sg' | 'cn' | 'us'
logging: true,
});
// Create a dashboard
const dashboardId = await client.createDashboard({
name: 'Sales Dashboard',
appToken: 'YOUR_APP_TOKEN',
});
// Add a bar chart
const chartBlock = ChartBlockBuilder.bar()
.dataSource('YOUR_APP_TOKEN', 'YOUR_TABLE_ID')
.xAxis({ fieldName: 'Category' })
.yAxis([{ fieldName: 'Revenue', aggregation: AggregationType.SUM }])
.title('Revenue by Category')
.colors(['#3b82f6', '#10b981', '#f59e0b'])
.build();
await client.addBlock('YOUR_APP_TOKEN', dashboardId, chartBlock);
```
### Available Block Types
#### 1. Chart Blocks
```typescript
import { ChartBlockBuilder, ChartType, AggregationType } from '@hypelab/hype-dash';
// Bar Chart
const barChart = ChartBlockBuilder.bar()
.dataSource(appToken, tableId)
.xAxis({ fieldName: 'Month' })
.yAxis([
{ fieldName: 'Sales', aggregation: AggregationType.SUM, label: 'Total Sales' },
{ fieldName: 'Orders', aggregation: AggregationType.COUNT, label: 'Order Count' }
])
.title('Monthly Sales Performance')
.showLegend(true)
.build();
// Line Chart
const lineChart = ChartBlockBuilder.line()
.dataSource(appToken, tableId)
.xAxis({ fieldName: 'Date' })
.yAxis([{ fieldName: 'Revenue', aggregation: AggregationType.SUM }])
.build();
// Pie Chart
const pieChart = ChartBlockBuilder.pie()
.dataSource(appToken, tableId)
.series({ fieldName: 'Category' })
.yAxis([{ fieldName: 'Amount', aggregation: AggregationType.SUM }])
.build();
```
#### 2. Metrics Blocks
```typescript
import { MetricsBlockBuilder, AggregationType } from '@hypelab/hype-dash';
const metrics = new MetricsBlockBuilder()
.dataSource(appToken, tableId)
.fieldName('Revenue')
.aggregation(AggregationType.SUM)
.title('Total Revenue')
.prefix('$')
.decimals(2)
.trendComparison(30, 'days')
.build();
```
#### 3. View Blocks
```typescript
import { ViewBlockBuilder, ViewType } from '@hypelab/hype-dash';
const tableView = ViewBlockBuilder.table()
.dataSource(appToken, tableId, viewId)
.title('Customer List')
.showToolbar(true)
.height(400)
.build();
const kanbanView = ViewBlockBuilder.kanban()
.dataSource(appToken, tableId, viewId)
.build();
```
#### 4. Text Blocks
```typescript
import { TextBlockBuilder } from '@hypelab/hype-dash';
const heading = new TextBlockBuilder()
.heading('Dashboard Overview')
.alignment('center')
.build();
const paragraph = new TextBlockBuilder()
.paragraph('Welcome to the sales dashboard.')
.build();
```
## MCP Server Usage
The SDK includes a Model Context Protocol server for Claude Code integration.
### Setup
Add to your `~/.claude.json` or Claude Code configuration:
```json
{
"mcpServers": {
"hype-dash": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@hypelab/hype-dash"],
"env": {
"LARK_API_KEY": "your-api-key-here",
"LARK_REGION": "sg"
}
}
}
}
```
### Available MCP Tools
- `create_dashboard` - Create a new dashboard
- `create_chart_block` - Add chart visualizations
- `create_metrics_block` - Add KPI metrics
- `create_view_block` - Add table/kanban views
- `create_text_block` - Add text content
- `list_dashboards` - List all dashboards
- `delete_dashboard` - Remove dashboards
### Usage with Claude Code
```
Create a sales dashboard with:
- Bar chart showing revenue by month
- KPI card for total revenue
- Table view of recent orders
```
Claude will use the MCP tools to create the dashboard automatically.
## Python SDK
The project includes a comprehensive Python SDK for managing Lark Base data. This allows you to:
- **Sync External Data**: Import data from TikTok Ads, databases, APIs, etc.
- **Batch Operations**: Efficiently create/update thousands of records
- **Data Transformation**: Transform and validate data before loading
- **Automatic Dashboard Updates**: Dashboards automatically reflect data changes
### Quick Example
```python
from lark_client import LarkBaseClient, LarkConfig
from data_manager import DataManager
# Initialize client
config = LarkConfig(
app_id=os.getenv('LARK_APP_ID'),
app_secret=os.getenv('LARK_APP_SECRET')
)
client = LarkBaseClient(config)
data_manager = DataManager(client)
# Sync TikTok campaign data
tiktok_data = fetch_tiktok_campaigns() # Your data source
result = data_manager.batch_upsert_records(
app_token='YOUR_APP_TOKEN',
table_id='YOUR_TABLE_ID',
records=tiktok_data,
key_field='campaign_id'
)
print(f"Synced {result['total']} campaigns")
# Your dashboards now show updated data automatically!
```
### Python SDK Features
- Full CRUD operations for tables, fields, and records
- Batch operations with automatic pagination
- Data validation and transformation utilities
- Incremental sync with timestamp tracking
- Field mapping for external data sources
- Rate limiting and error handling
- Comprehensive logging
**See [Python SDK Documentation](python/README.md) for complete guide.**
### Workflow: Python + TypeScript
1. **Python**: Manage data (create tables, sync external sources, batch updates)
2. **TypeScript**: Create beautiful dashboards to visualize the data
3. **Automatic**: Dashboards update automatically when data changes
```python
# 1. Python: Sync data
data_manager.batch_upsert_records(...)
```
```typescript
// 2. TypeScript: Create dashboard
const chart = ChartBlockBuilder.bar()
.dataSource(appToken, tableId)
.build();
```
## Configuration
### Client Options
```typescript
const client = new LarkDashboardClient({
apiKey: string; // Required: Lark API key
region?: 'sg' | 'cn' | 'us'; // Default: 'sg'
apiUrl?: string; // Optional: Custom API URL
logging?: boolean; // Default: false
timeout?: number; // Default: 30000ms
maxRetries?: number; // Default: 3
retryDelay?: number; // Default: 1000ms
});
```
### Environment Variables
```bash
LARK_API_KEY=your-api-key
LARK_REGION=sg
LARK_LOGGING=true
```
## Advanced Features
### Batch Operations
```typescript
const blocks = [
ChartBlockBuilder.bar().dataSource(appToken, tableId).build(),
MetricsBlockBuilder.sum('Revenue').dataSource(appToken, tableId).build(),
ViewBlockBuilder.table().dataSource(appToken, tableId, viewId).build(),
];
const results = await client.batchCreateBlocks(appToken, blocks);
```
### Filtering
```typescript
import { FilterOperator, FilterConjunction } from '@hypelab/hype-dash';
const chart = ChartBlockBuilder.bar()
.dataSource(appToken, tableId)
.filters(FilterConjunction.AND, [
{ fieldName: 'Status', operator: FilterOperator.IS, value: 'Active' },
{ fieldName: 'Revenue', operator: FilterOperator.GT, value: 1000 }
])
.build();
```
### Error Handling
```typescript
import { ValidationError } from '@hypelab/hype-dash';
try {
await client.addBlock(appToken, dashboardId, block);
} catch (error) {
if (error instanceof ValidationError) {
console.error('Validation failed:', error.message);
} else {
console.error('API error:', error);
}
}
```
## API Reference
### LarkDashboardClient
- `createDashboard(dashboard: Dashboard): Promise<string>`
- `addBlock(appToken: string, dashboardId: string, block: DashboardBlock): Promise<string>`
- `updateBlock(appToken: string, blockId: string, block: Partial<DashboardBlock>): Promise<void>`
- `deleteBlock(appToken: string, blockId: string): Promise<void>`
- `listBlocks(appToken: string): Promise<DashboardBlock[]>`
- `batchCreateBlocks(appToken: string, blocks: DashboardBlock[]): Promise<BatchOperationResult[]>`
### Builders
- `ChartBlockBuilder` - Create chart visualizations
- `MetricsBlockBuilder` - Create KPI metrics
- `ViewBlockBuilder` - Create data views
- `TextBlockBuilder` - Create text blocks
- `ListBlockBuilder` - Create list blocks (2025)
- `TabPageBlockBuilder` - Create tab pages (2025)
## Examples
See the `/examples` directory for complete examples:
- `basic-dashboard.ts` - Simple dashboard creation
- `complete-dashboard.ts` - Full-featured dashboard
- `multi-source-dashboard.ts` - Multiple data sources
- `realtime-dashboard.ts` - Real-time data updates
## TypeScript Support
The SDK is written in TypeScript and provides comprehensive type definitions:
```typescript
import type {
DashboardBlock,
ChartConfig,
MetricsConfig,
ViewConfig,
ChartType,
ViewType,
AggregationType,
} from '@hypelab/hype-dash';
```
## Requirements
### TypeScript/JavaScript
- Node.js >= 16.0.0
- TypeScript >= 5.0.0 (for TypeScript projects)
### Python
- Python >= 3.8
- See [python/requirements.txt](python/requirements.txt) for dependencies
## Troubleshooting
### Common Issues
**Authentication Errors**
- Verify your LARK_API_KEY is correct
- Check API key permissions in Lark admin console
- Ensure region matches your Lark workspace ('sg', 'cn', or 'us')
**Network Errors**
- Check firewall settings
- Verify network connectivity to Lark API
- Try increasing timeout in client config
**Validation Errors**
- Ensure required fields are provided
- Check data types match API expectations
- Verify field names exist in your Lark tables
## Contributing
Contributions are welcome! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.
## License
MIT License - see [LICENSE](LICENSE) file for details.
## Support
- GitHub Issues: https://github.com/hypelab/hype-dash/issues
- Email: dev@hypelab.com
## Changelog
See [CHANGELOG.md](CHANGELOG.md) for version history and updates.
