Log parse, filter, analyze for AI agents
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Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-rog0x-log": {
"args": [
"-y",
"@rog0x/mcp-log-tools"
],
"command": "npx"
}
}
}From the project's GitHub README.
Log analysis and processing tools for AI agents, exposed via the Model Context Protocol (MCP).
Parse log content in common formats: JSON logs, Apache/Nginx access logs, syslog, and structured logs. Supports custom regex patterns with named capture groups. Extracts timestamp, level, message, source, and additional structured fields.
Filter parsed log entries by:
Returns matched entries along with level occurrence counts.
Analyze log patterns to surface operational insights:
Convert between log formats and produce reports:
Compute comprehensive log statistics:
npm install
npm run build
Add to your claude_desktop_config.json:
{
"mcpServers": {
"log-tools": {
"command": "node",
"args": ["path/to/mcp-log-tools/dist/index.js"]
}
}
}
| Format | Example |
|---|---|
| JSON | {"timestamp":"2024-01-15T10:30:00Z","level":"ERROR","message":"Connection failed"} |
| Apache/Nginx | 127.0.0.1 - frank [10/Oct/2000:13:55:36 -0700] "GET /index.html HTTP/1.1" 200 2326 |
| Syslog | Jan 1 00:00:00 hostname process[1234]: Something happened |
| Structured | 2024-01-15T10:30:00.000Z [ERROR] [ModuleName] Something failed |
| Custom | Any format using a regex with named capture groups |
MIT
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