CensusChat API Integration Guide

MCP Layer, SQL Validation & Census API Flow

Overview

CensusChat’s backend API serves as the intelligent middleware between natural language queries and Census Bureau data. The system uses Model Context Protocol (MCP) for SQL validation and Claude Sonnet for natural language processing.

Architecture Flow

Frontend Query → Backend API → MCP Validation → Claude Translation → Census API → Response Processing → Frontend Display

API Endpoints

Core Query Endpoint

POST /api/v1/queries

Request Format:

{
  "query": "Show me Medicare eligible seniors in Florida with income over $50k",
  "options": {
    "format": "table|chart|export",
    "limit": 1000,
    "includeMetadata": true
  }
}

Response Format:

{
  "success": true,
  "message": "Found 1,234,567 records matching your query",
  "data": [
    {
      "geography": "Florida",
      "seniors_count": 1234567,
      "medicare_eligible": 987654,
      "high_income_seniors": 456789
    }
  ],
  "metadata": {
    "queryTime": 1.8,
    "totalRecords": 1234567,
    "dataSource": "ACS 2022 5-Year",
    "confidenceLevel": 0.95,
    "marginOfError": 2.3
  },
  "sql": {
    "validated": true,
    "query": "SELECT geography, COUNT(*) as seniors_count...",
    "explain": "Query retrieves population data filtered by age 65+, Medicare eligibility, and income thresholds"
  }
}

Authentication Endpoints

POST /api/v1/auth/login POST /api/v1/auth/logout
GET /api/v1/auth/profile

Query Management

GET /api/v1/queries/history - User query history POST /api/v1/queries/save - Save query for reuse DELETE /api/v1/queries/{id} - Delete saved query

Data Export

POST /api/v1/export/excel - Generate Excel file POST /api/v1/export/csv - Generate CSV file POST /api/v1/export/pdf - Generate PDF report

MCP Integration

SQL Validation Layer

The MCP (Model Context Protocol) layer provides robust SQL validation before query execution:

Validation Process:

  1. Syntax Checking: Validates SQL syntax correctness
  2. Security Scanning: Prevents SQL injection attacks
  3. Performance Analysis: Estimates query complexity and execution time
  4. Data Compliance: Ensures queries comply with Census data usage policies

MCP Configuration:

const mcpValidator = new MCPValidator({
  maxComplexity: 1000,
  allowedTables: ['census_data', 'geography', 'demographics'],
  prohibitedOperations: ['DROP', 'DELETE', 'UPDATE', 'INSERT'],
  timeoutMs: 5000
});

Validation Response

{
  "valid": true,
  "confidence": 0.98,
  "estimatedRows": 125000,
  "estimatedTime": 1.2,
  "warnings": [],
  "suggestions": [
    "Consider adding geographic filters to improve performance"
  ]
}

Claude Integration

Natural Language Processing

Claude Sonnet 4 translates natural language queries into SQL:

Translation Process:

  1. Intent Recognition: Identifies query type and data requirements
  2. Entity Extraction: Extracts geographic, demographic, and temporal filters
  3. SQL Generation: Creates optimized SQL query
  4. Context Preservation: Maintains conversation context for follow-up queries

Claude Configuration:

const claudeClient = new AnthropicClient({
  apiKey: process.env.ANTHROPIC_API_KEY,
  model: 'claude-3-5-sonnet-20241022',
  maxTokens: 1000,
  temperature: 0.1 // Low temperature for consistent SQL generation
});

Prompt Template

const QUERY_TRANSLATION_PROMPT = `
You are a healthcare demographics expert. Translate this natural language query into SQL for Census data:

Query: "${userQuery}"

Available tables:
- census_data (geography_code, variable_code, value, margin_of_error, year)
- geography (code, name, type, state_code)
- variables (code, label, concept, group)

Healthcare context:
- Medicare eligibility typically starts at age 65
- Senior care focuses on 65+ population
- Income thresholds often reference poverty guidelines

Generate SQL that:
1. Filters for relevant demographics
2. Includes geographic specificity
3. Provides statistical confidence measures
4. Optimizes for performance

SQL Query:
`;

Census API Integration

Service Configuration

class CensusApiService {
  private baseURL = 'https://api.census.gov/data';
  private apiKey = process.env.CENSUS_API_KEY;
  private timeout = 30000; // 30 second timeout

  async queryData(params: CensusQueryParams): Promise<CensusResponse> {
    const url = this.buildQueryURL(params);
    const response = await axios.get(url, {
      timeout: this.timeout,
      headers: { 'User-Agent': 'CensusChat/1.0' }
    });
    return this.processResponse(response.data);
  }
}

Error Handling

const handleCensusAPIError = (error: AxiosError) => {
  if (error.response?.status === 429) {
    throw new APIError('RATE_LIMIT', 'Census API rate limit exceeded');
  } else if (error.response?.status === 400) {
    throw new APIError('INVALID_QUERY', 'Invalid Census API parameters');
  } else if (error.code === 'ENOTFOUND') {
    throw new APIError('NETWORK', 'Cannot connect to Census API');
  } else {
    throw new APIError('UNKNOWN', 'Census API error');
  }
};

Data Processing Pipeline

Response Transformation

interface ProcessingPipeline {
  // 1. Raw Census API response
  censusData: CensusAPIResponse;
  
  // 2. Data validation and cleaning
  validateData(data: any[]): ValidationResult;
  
  // 3. Statistical calculations
  calculateStatistics(data: any[]): StatisticalSummary;
  
  // 4. Format for frontend consumption
  formatForDisplay(data: any[]): DisplayData;
  
  // 5. Generate export formats
  generateExports(data: any[]): ExportFormats;
}

Data Validation

const validateCensusData = (data: any[]): ValidationResult => {
  const validation = {
    totalRecords: data.length,
    nullValues: countNullValues(data),
    outliers: detectOutliers(data),
    dataQuality: calculateQualityScore(data),
    marginOfError: extractMarginOfError(data)
  };
  
  return {
    isValid: validation.dataQuality > 0.8,
    warnings: generateWarnings(validation),
    metadata: validation
  };
};

Caching Strategy

Redis Cache Implementation

class QueryCache {
  private redis = new Redis(process.env.REDIS_URL);
  private defaultTTL = 3600; // 1 hour

  async get(queryHash: string): Promise<CachedResult | null> {
    const cached = await this.redis.get(`query:${queryHash}`);
    return cached ? JSON.parse(cached) : null;
  }

  async set(queryHash: string, result: any, ttl = this.defaultTTL): Promise<void> {
    await this.redis.setex(`query:${queryHash}`, ttl, JSON.stringify(result));
  }

  generateHash(query: string, params: any): string {
    return crypto
      .createHash('sha256')
      .update(JSON.stringify({ query, params }))
      .digest('hex');
  }
}

Cache Invalidation

  • Time-based: Automatic expiration after 1 hour
  • Version-based: Clear cache when Census data updates
  • User-based: Separate cache per user for personalized queries

Performance Monitoring

Query Performance Tracking

const trackQueryPerformance = async (queryId: string, startTime: number) => {
  const endTime = Date.now();
  const duration = endTime - startTime;
  
  await analytics.track('query_performance', {
    queryId,
    duration,
    timestamp: new Date().toISOString(),
    success: true
  });
  
  // Alert if performance degrades
  if (duration > 5000) {
    logger.warn(`Slow query detected: ${queryId} took ${duration}ms`);
  }
};

Error Rate Monitoring

const errorRateMonitor = {
  track: (error: APIError) => {
    metrics.increment('api.errors', {
      type: error.type,
      endpoint: error.endpoint
    });
  },
  
  alert: (errorRate: number) => {
    if (errorRate > 0.05) { // 5% error rate
      alerting.send('High API error rate detected');
    }
  }
};

Security Measures

API Key Management

const apiKeyRotation = {
  primary: process.env.CENSUS_API_KEY_PRIMARY,
  secondary: process.env.CENSUS_API_KEY_SECONDARY,
  
  getCurrentKey(): string {
    // Rotate keys based on time or usage
    return this.shouldRotate() ? this.secondary : this.primary;
  },
  
  shouldRotate(): boolean {
    // Rotate every 24 hours or after 10k requests
    return Date.now() % (24 * 60 * 60 * 1000) < 1000;
  }
};

Rate Limiting

const rateLimiter = rateLimit({
  windowMs: 15 * 60 * 1000, // 15 minutes
  max: 100, // Limit each IP to 100 requests per windowMs
  message: 'Too many requests, please try again later',
  standardHeaders: true,
  legacyHeaders: false,
});

Development and Testing

Mock API Development

// Development mode: use mock Census API
if (process.env.NODE_ENV === 'development') {
  const mockCensusAPI = new MockCensusAPI({
    responseDelay: 500,
    errorRate: 0.05,
    dataVariability: true
  });
}

Integration Testing

describe('API Integration', () => {
  test('processes natural language query', async () => {
    const query = "Medicare seniors in California";
    const response = await queryAPI(query);
    
    expect(response.success).toBe(true);
    expect(response.data).toBeDefined();
    expect(response.sql.validated).toBe(true);
  });
});

Deployment Configuration

Environment Variables

# Production environment
ANTHROPIC_API_KEY=sk-ant-api03-YOUR-KEY-HERE
CENSUS_API_KEY=your-census-api-key-here
REDIS_URL=redis://localhost:6379
DATABASE_URL=postgresql://user:pass@host:port/db
MCP_ENDPOINT=https://mcp.service.url
LOG_LEVEL=info

Health Checks

const healthCheck = {
  async checkCensusAPI(): Promise<boolean> {
    try {
      await censusAPI.get('/data');
      return true;
    } catch {
      return false;
    }
  },
  
  async checkMCP(): Promise<boolean> {
    try {
      await mcpValidator.validate('SELECT 1');
      return true;
    } catch {
      return false;
    }
  },
  
  async checkClaude(): Promise<boolean> {
    try {
      await claudeClient.messages.create({
        model: 'claude-3-5-sonnet-20241022',
        messages: [{ role: 'user', content: 'test' }],
        max_tokens: 10
      });
      return true;
    } catch {
      return false;
    }
  }
};

Future Enhancements

Planned Integrations

  • GraphQL API: More flexible data querying
  • WebSocket Support: Real-time query updates
  • Batch Processing: Handle multiple queries efficiently
  • Machine Learning: Improve query translation accuracy
  • Data Streaming: Handle large result sets efficiently

Performance Improvements

  • Query Optimization: Automatic query plan analysis
  • Predictive Caching: Cache likely follow-up queries
  • Connection Pooling: Optimize database connections
  • CDN Integration: Cache static responses geographically

This API integration provides a robust, scalable foundation for CensusChat’s core functionality while maintaining security, performance, and reliability standards required for enterprise healthcare applications.