LogAnalyzer MCP Server

Instructions

Implementation Reference

• src/server.ts:346-367 (handler)

  MCP tool handler for 'analyze_log': validates input, calls LogAnalyzer.analyzeLogs, formats MCPToolResult response

  private async handleAnalyzeLog(args: any): Promise<MCPToolResult> {
    const { logText, logFormat = 'auto', contextLines = 50 } = args;
  
    if (!logText || typeof logText !== 'string') {
      throw new Error('logText is required and must be a string');
    }
  
    const analysis = await this.logAnalyzer.analyzeLogs(logText, {
      logFormat,
      contextLines
    });
  
    return {
      success: true,
      data: analysis,
      metadata: {
        processedAt: new Date(),
        logLength: logText.length,
        format: logFormat
      }
    };
  }

• src/tools/logAnalyzer.ts:19-36 (helper)

  Core implementation: preprocesses logs, generates AI prompt for Gemini, parses response into structured LogAnalysis

  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'}`);
    }
  }

• src/server.ts:81-101 (schema)

  Input schema validation for analyze_log tool parameters

  inputSchema: {
    type: 'object',
    properties: {
      logText: {
        type: 'string',
        description: 'Log content to analyze'
      },
      logFormat: {
        type: 'string',
        enum: ['auto', 'json', 'plain'],
        default: 'auto',
        description: 'Format of the log content'
      },
      contextLines: {
        type: 'number',
        default: 50,
        description: 'Number of context lines to include around errors'
      }
    },
    required: ['logText']
  }

• src/server.ts:78-102 (registration)

  Tool descriptor registration in ListToolsRequestSchema handler, including dispatch case at line 180

  {
    name: 'analyze_log',
    description: 'Analyze error logs and provide root cause analysis with AI-powered insights',
    inputSchema: {
      type: 'object',
      properties: {
        logText: {
          type: 'string',
          description: 'Log content to analyze'
        },
        logFormat: {
          type: 'string',
          enum: ['auto', 'json', 'plain'],
          default: 'auto',
          description: 'Format of the log content'
        },
        contextLines: {
          type: 'number',
          default: 50,
          description: 'Number of context lines to include around errors'
        }
      },
      required: ['logText']
    }
  },