AI日志分析MCP服务

LogAnalyzer MCP Server

AI-powered log analysis for your editor. Paste a log or point at a log file, and get the root cause, prioritized fixes, and ready-to-run debug commands, right inside Claude, Cursor, or any other MCP client.

Features

• Root-cause analysis: an LLM (Google Gemini or Anthropic Claude) reads your logs and explains what went wrong, with a confidence score.
• Actionable fixes: prioritized suggestions plus copy-paste debug commands.
• Live monitoring: watch log files and catch new errors as they're written.
• Stack trace parsing: Node/V8, Java, and Python traces are parsed into structured fields.
• Error history: every analysis is saved to a local SQLite database you can query by file, severity, and date.
• Works without an API key: with no key, the server still runs and falls back to local pattern matching.

Quick start

You need Node.js 18+ and, for AI analysis, an API key from Google AI Studio or the Anthropic Console.

Claude Code

claude mcp add loganalyzer -e LLM_PROVIDER=anthropic -e ANTHROPIC_API_KEY=your_key -- npx -y loganalyzer-mcp

Claude Desktop, Cursor, and other MCP clients

Add this to your client's MCP config (claude_desktop_config.json for Claude Desktop, ~/.cursor/mcp.json for Cursor):

{
  "mcpServers": {
    "loganalyzer": {
      "command": "npx",
      "args": ["-y", "loganalyzer-mcp"],
      "env": {
        "GEMINI_API_KEY": "your_gemini_api_key"
      }
    }
  }
}

To use Claude instead of Gemini, replace the env block with:

"env": {
  "LLM_PROVIDER": "anthropic",
  "ANTHROPIC_API_KEY": "your_anthropic_api_key"
}

Prefer a global install? Run npm install -g loganalyzer-mcp and use "command": "loganalyzer-mcp" with no args.

Restart your client, then try asking:

Debug these logs and tell me how to fix them: <paste logs>
Start watching /var/log/app.log for errors
Show me all critical errors from the last 24 hours

Tools

The server also exposes three MCP resources: loganalyzer://rapid-debug, loganalyzer://recent-errors, and loganalyzer://watched-files.

Configuration

All settings are environment variables, set in your MCP client's env block or in a .env file.

No API key? The server still starts. It logs a warning to stderr, disables AI analysis, and the tools keep working with local pattern matching, file watching, and history.

Troubleshooting

• The server exits right away when I run it in a terminal. That's expected. MCP servers talk over stdin/stdout and are started by your MCP client, not run by hand.
• Analysis says "AI analysis disabled". No API key matches LLM_PROVIDER. Check that the key is in your client's env block and restart the client.
• Model not found errors. Your key may not have access to the default model. Set LLM_MODEL to one it does.
• Install fails while building better-sqlite3. It's a native module. Make sure you're on a current Node.js LTS release; prebuilt binaries are downloaded for most platforms.
• File watching doesn't pick anything up. Use an absolute path and check that the file is readable by the user your MCP client runs as.

Development

git clone https://github.com/ChiragPatankar/loganalyzer-mcp.git
cd loganalyzer-mcp
npm ci
npm run build
npm test

npm run dev runs the server from source and npm run analyze <logfile> runs a quick CLI analysis. To test with an MCP client, point it at node /absolute/path/to/loganalyzer-mcp/dist/src/server.js.

More guides:

• Cursor integration
• Example usage
• Hardening notes
• Changelog

Contributing

Issues and pull requests are welcome. Please run npm run build && npm test before opening a PR, and open an issue first for larger changes.

License

MIT © Chirag Patankar