DevOps Tool

Log Parser

Parse and analyze any log format instantly. Auto-detects JSON, Syslog, Apache, Nginx, Docker, and application logs with structured output, level breakdown, and error pattern analysis.

Install

Get the CLI Tool

Run the log parser locally as an MCP server, or try it online below.

npx @clinetools/log-parser
Requires Node.js 18+
  • 8 formats — JSON, Syslog, Apache, Nginx, Docker/K8s, app logs, and more
  • Auto-detects format from log content patterns
  • Level breakdown with INFO, WARN, ERROR, DEBUG, FATAL counts
  • Error pattern grouping — clusters similar errors automatically
  • Zero config — just run with npx
Tutorial

How to Use It

Three ways to parse your logs — pick the one that fits your workflow.

1

Try Online

Use the interactive demo below to paste raw logs and parse them — no install needed.

↓ Jump to interactive demo
2

Use via CLI

Run as a local MCP server and connect any MCP-compatible client.

npx @clinetools/log-parser
3

Add to Cline / Claude Code

Add the tool to your MCP settings for instant log analysis from your AI assistant.

"log-parser": { "command": "npx", "args": ["@clinetools/log-parser"] }

MCP Client Configuration (Cline) 

{
  "mcpServers": {
    "log-parser": {
      "command": "npx",
      "args": ["@clinetools/log-parser"]
    }
  }
}

Claude Code Configuration 

# In your project's .mcp.json:
{
  "mcpServers": {
    "log-parser": {
      "command": "npx",
      "args": ["@clinetools/log-parser"]
    }
  }
}

Example: Parse Application Logs 

// Call the tool with raw log text:
parse_logs({
  logs: "[2026-02-10 14:23:01] INFO: Server started\n[2026-02-10 14:23:15] ERROR: DB connection failed"
})

// Output:
{
  "format": "Simple timestamped log",
  "totalLines": 2,
  "parsedLines": 2,
  "levelBreakdown": { "INFO": 1, "ERROR": 1 },
  "errorPatterns": [
    { "pattern": "DB connection failed", "count": 1 }
  ],
  "entries": [...]
}
Live Demo

Try It Online

Paste raw logs below and parse them instantly. Or try one of our demo scenarios.

Paste Logs to Parse

Supports JSON, Syslog, Apache, Nginx, Docker/K8s, and app logs

Try a demo:

Paste raw logs and click Parse Logs to see structured results.

Level Breakdown

Parsed Entries

Learn

Why Log Parsing Matters

Logs are the black box of your application. Parsing them properly is the first step to understanding what went wrong.

Structured vs Unstructured

Structured logs (JSON) are machine-readable from the start. Unstructured logs (plain text) require parsing to extract timestamps, levels, and context. A good parser handles both transparently.

Log Levels

DEBUG, INFO, WARN, ERROR, FATAL — each level tells a different story. Level breakdown gives you an instant health snapshot: a spike in ERROR or WARN often indicates a problem before alerts fire.

Centralized Logging

In distributed systems, logs from dozens of services need to be parsed, normalized, and correlated. Consistent parsing across formats (Nginx, app, Docker) is the foundation for tools like ELK, Loki, or Datadog.

Log Retention

Raw logs are expensive to store. Parsing and analyzing logs before archival lets you extract key metrics, group error patterns, and reduce storage costs by keeping only what matters for future debugging.

Parse Every Log

Our Pro plan includes real-time log streaming, alerting on error patterns, and cross-service correlation.

View Plans