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Raistlin82

SAP OData to MCP Server

by Raistlin82

smart-data-analysis

Analyze SAP data patterns, trends, and anomalies to generate actionable business insights using AI-powered statistical analysis and visualization recommendations.

Instructions

Analyze SAP data patterns, trends, and generate actionable business insights with AI-powered statistical analysis. Provides automated data exploration and visualization recommendations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesArray of data records to analyze - each record is a key-value object
analysisTypeYesType of analysis to perform
businessContextNoBusiness context for the analysis
entityTypeYesType of SAP entity being analyzed

Implementation Reference

  • The execute method implements the core logic of the 'smart-data-analysis' tool. It uses an AI integration service to analyze provided SAP data based on the specified analysis type (trend, anomaly, forecast, correlation), generating insights, recommendations, and confidence scores.
    async execute(params: any): Promise<any> {
      try {
        logger.info('Starting smart data analysis', {
          recordCount: params.data.length,
          analysisType: params.analysisType,
          entityType: params.entityType,
        });
    
        const prompt = `Analyze this ${params.entityType} data for ${params.analysisType} patterns and business insights`;
    
        const analysis = await aiIntegration.analyzeData(prompt, params.data, params.analysisType);
    
        const insights = analysis.insights.map(
          (insight: any) => `${insight.title}: ${insight.description} (${insight.impact} impact)`
        );
    
        const recommendations = analysis.recommendations.map(
          (rec: any) => `${rec.title}: ${rec.description} (Priority: ${rec.priority})`
        );
    
        return {
          success: true,
          analysis,
          insights,
          recommendations,
          confidence: analysis.confidence,
        };
      } catch (error) {
        const errorMessage = error instanceof Error ? error.message : 'Unknown error';
        logger.error('Smart data analysis failed', { error: errorMessage });
    
        return {
          success: false,
          error: errorMessage,
        };
      }
    }
  • The inputSchema property defines the TypeScript schema for tool inputs, specifying required data array of SAP records, analysis type enum, optional business context, and entity type.
    inputSchema = {
      type: 'object' as const,
      properties: {
        data: {
          type: 'array' as const,
          description: 'Array of data records to analyze - each record is a key-value object',
          items: {
            type: 'object' as const,
            description: 'Data record with flexible schema for SAP entity analysis',
            additionalProperties: true,
          },
        },
        analysisType: {
          type: 'string' as const,
          enum: ['trend', 'anomaly', 'forecast', 'correlation'] as const,
          description: 'Type of analysis to perform',
        },
        businessContext: {
          type: 'string' as const,
          description: 'Business context for the analysis',
        },
        entityType: {
          type: 'string' as const,
          description: 'Type of SAP entity being analyzed',
        },
      },
      required: ['data', 'analysisType', 'entityType'],
    };
  • The SmartDataAnalysisTool instance is created and exported as part of the aiEnhancedTools array, which is used for registering AI-enhanced tools with the MCP server.
    export const aiEnhancedTools = [
      new NaturalQueryBuilderTool(),
      new SmartDataAnalysisTool(),
      new QueryPerformanceOptimizerTool(),
      new BusinessProcessInsightsTool(),
    ];

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