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CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

This is the Apex Log MCP Server - a Model Context Protocol (MCP) server for Apex Log Analysis. It provides AI agents with tools to analyze Salesforce Apex debug logs for performance bottlenecks and optimization opportunities.

Development Commands

# Install dependencies
pnpm install

# Build the TypeScript project
pnpm run build

# Development with watch mode
pnpm run dev

# Run the server standalone
pnpm start

Architecture

Core Components

  • src/index.ts: Main MCP server implementation (ApexLogServer class)

    • Implements 4 MCP tools: analyze_apex_log_performance, get_apex_log_summary, find_performance_bottlenecks, execute_anonymous
    • Uses stdio transport for communication
    • Handles file validation, log parsing, analysis, and anonymous Apex execution

  • src/ApexLogParser.ts: Complex log parsing engine (33k+ tokens)

    • Exports parse() function and ApexLogParser class
    • Handles Apex debug log format parsing into structured data
    • Tracks governor limits, performance metrics, and log issues

Key Data Structures

  • ApexLog: Root log structure with duration, governor limits, namespaces
  • LogLine: Individual log entries with hierarchical relationships
  • SlowMethod: Performance analysis result with timing and resource usage
  • GovernorLimits: Salesforce platform limits tracking

MCP Integration

This server is designed to integrate with the Apex Log Analyzer VS Code extension:

  • Registered automatically by the extension
  • Communicates via MCP protocol over stdio
  • Provides structured JSON responses for AI analysis

TypeScript Configuration

  • Target: ES2022
  • Module: ESNext with Node resolution
  • Strict mode enabled
  • Output to dist/ directory
  • Source maps and declarations generated

File Structure

src/
  index.ts          # MCP server implementation
  ApexLogParser.ts  # Log parsing engine
dist/               # Compiled JavaScript output

Tools

The server provides four main capabilities:

  1. Performance Analysis: Identifies slowest methods with detailed metrics
  2. Log Summary: High-level execution statistics and governor limit usage
  3. Bottleneck Detection: Analyzes CPU, database, and method performance patterns
  4. Execute Anonymous: Executes anonymous Apex code snippets, saves the debug log to a file, and returns a summary with the file path

Log analysis tools (1-3) accept absolute file paths to .log files and return structured JSON for AI processing. Anonymous execution (4) accepts multi-line strings containing Apex, saves the resulting debug log to a local file (default: .apex-log-mcp/ in the project root), and returns a summary with the file path. The outputDir parameter overrides the default save location. It supports an optional debugLevel parameter to configure trace flag log levels per category or set all categories at once. The execute_anonymous tool is disabled by default and only registered when --allowed-orgs is configured. The allowlist supports special tokens (ALLOW_ALL_ORGS, DEFAULT_TARGET_ORG, DEFAULT_TARGET_DEV_HUB) as well as org usernames/aliases. Aliases are resolved to usernames for matching. The response includes the org alias alongside the username when available.