LogAnalyzer MCP Server

import { GoogleGenerativeAI } from '@google/generative-ai'; import { LogAnalysis, LogParsingOptions } from '../types.js'; import { LogUtils } from '../utils.js'; export class LogAnalyzer { private genAI: GoogleGenerativeAI; private model: any; constructor() { const apiKey = process.env.GEMINI_API_KEY; if (!apiKey) { throw new Error('GEMINI_API_KEY environment variable is required'); } this.genAI = new GoogleGenerativeAI(apiKey); this.model = this.genAI.getGenerativeModel({ model: "gemini-1.5-flash" }); } async analyzeLogs(logText: string, options: LogParsingOptions): Promise<LogAnalysis> { // Pre-process the log content const processedContent = this.preprocessLogs(logText, options); // Build analysis prompt const prompt = this.buildAnalysisPrompt(processedContent, options); try { // Generate analysis using Gemini const result = await this.model.generateContent(prompt); const response = await result.response; // Parse and structure the response return this.parseResponse(response.text(), logText); } catch (error) { throw new Error(`Failed to analyze logs: ${error instanceof Error ? error.message : 'Unknown error'}`); } } private preprocessLogs(logText: string, options: LogParsingOptions): string { let processed = logText; // Detect format if auto if (options.logFormat === 'auto') { const detectedFormat = LogUtils.detectLogFormat(logText); options.logFormat = detectedFormat; } // Extract error patterns for better focus const errorPatterns = LogUtils.extractErrorPatterns(logText); if (errorPatterns.length > 0) { // Include error sections plus some context processed = errorPatterns.join('\n---\n'); } // Truncate if too large processed = LogUtils.truncateContent(processed); return processed; } private buildAnalysisPrompt(logContent: string, options: LogParsingOptions): string { return `You are an expert log analyst. Analyze the following ${options.logFormat} logs and provide a structured analysis. Log Content: \`\`\` ${logContent} \`\`\` Please provide your analysis in the following JSON format: { "rootCause": "Brief explanation of the main issue identified", "confidence": "number between 0-100 indicating confidence in the analysis", "suggestedFixes": ["array", "of", "specific", "actionable", "solutions"], "relatedErrors": ["array", "of", "related", "error", "messages", "or", "patterns"], "followUpQuestions": ["array", "of", "questions", "to", "help", "debug", "further"], "metadata": { "errorType": "type of error (e.g., 'runtime', 'configuration', 'network', 'database')", "severity": "one of: 'low', 'medium', 'high', 'critical'", "lineNumbers": [1, 2, 3], "stackTrace": "extracted stack trace if available" } } Focus on: 1. Identifying the root cause of errors 2. Providing actionable solutions 3. Extracting relevant context and patterns 4. Assessing the severity and impact 5. Suggesting follow-up investigations Be specific and practical in your recommendations. If multiple errors are present, focus on the most critical ones.`; } private parseResponse(responseText: string, originalLogText: string): LogAnalysis { try { // Try to extract JSON from the response const jsonMatch = responseText.match(/\{[\s\S]*\}/); if (!jsonMatch) { throw new Error('No JSON found in response'); } const parsed = JSON.parse(jsonMatch[0]); // Validate and structure the response const analysis: LogAnalysis = { rootCause: parsed.rootCause || 'Unable to determine root cause', confidence: Math.min(100, Math.max(0, parsed.confidence || 0)), suggestedFixes: Array.isArray(parsed.suggestedFixes) ? parsed.suggestedFixes : [], relatedErrors: Array.isArray(parsed.relatedErrors) ? parsed.relatedErrors : [], followUpQuestions: Array.isArray(parsed.followUpQuestions) ? parsed.followUpQuestions : [], metadata: { errorType: parsed.metadata?.errorType || 'unknown', severity: this.validateSeverity(parsed.metadata?.severity), timestamp: new Date(), lineNumbers: Array.isArray(parsed.metadata?.lineNumbers) ? parsed.metadata.lineNumbers : [], stackTrace: parsed.metadata?.stackTrace || LogUtils.extractStackTraces(originalLogText).join('\n') } }; return analysis; } catch (error) { // Fallback analysis if parsing fails return this.createFallbackAnalysis(responseText, originalLogText); } } private validateSeverity(severity: string): 'low' | 'medium' | 'high' | 'critical' { const validSeverities = ['low', 'medium', 'high', 'critical']; return validSeverities.includes(severity) ? severity as any : 'medium'; } private createFallbackAnalysis(responseText: string, originalLogText: string): LogAnalysis { const errorPatterns = LogUtils.extractErrorPatterns(originalLogText); const stackTraces = LogUtils.extractStackTraces(originalLogText); return { rootCause: 'AI analysis failed, but errors detected in logs', confidence: 30, suggestedFixes: [ 'Review the error patterns identified', 'Check application configuration', 'Examine stack traces for debugging' ], relatedErrors: errorPatterns.slice(0, 3), followUpQuestions: [ 'What actions were being performed when the error occurred?', 'Has this error happened before?', 'Were there any recent changes to the system?' ], metadata: { errorType: 'unknown', severity: errorPatterns.length > 5 ? 'high' : 'medium', timestamp: new Date(), stackTrace: stackTraces.join('\n') } }; } }