About io.github.rog0x/log
io.github.rog0x/log is an MCP server published by rog0x in the Developer Tools category: log parse, filter, analyze for AI agents.
The repository has 1 stars and 0 forks, with the last commit 7 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
claude mcp add io-github-rog0x-log -- npx -y @rog0x/mcp-log-toolsnpx -y @rog0x/mcp-log-toolsThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Tools (5)
analyze_logsAnalyze log patterns: top 10 most frequent errors, error rate over time, request volume per hour, slowest endpoints (from access logs), and anomaly detection (sudden spikes/drops).
Parameters not published.
filter_logsFilter log entries by level, date range, keyword, regex pattern, or source. Returns matched entries and level counts.
Parameters not published.
format_logsConvert logs between formats (JSON, plain text, CSV, table). Supports colorization by level, field extraction, and summary report generation.
Parameters not published.
log_statsCompute log statistics: total lines, lines per level, date range, unique IPs, top user agents, status code distribution, throughput, and more.
Parameters not published.
parse_logsParse log content in common formats (JSON, Apache/Nginx, syslog, structured, or custom regex). Returns structured entries with timestamp, level, message, source, and extracted fields.
Parameters not published.
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README
@rog0x/mcp-log-tools
Log analysis and processing tools for AI agents, exposed via the Model Context Protocol (MCP).
Tools
parse_logs
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_logs
Filter parsed log entries by:
- Log level (ERROR, WARN, INFO, DEBUG)
- Date range (ISO 8601)
- Keyword search (case-insensitive)
- Regex pattern matching
- Source/logger name
Returns matched entries along with level occurrence counts.
analyze_logs
Analyze log patterns to surface operational insights:
- Top 10 most frequent errors (normalized)
- Error rate over time (hourly buckets)
- Request volume per hour
- Slowest endpoints (from HTTP access logs)
- Anomaly detection (sudden spikes or drops using standard deviation)
format_logs
Convert between log formats and produce reports:
- JSON to plain text, plain to JSON, CSV, or table
- ANSI colorization by log level
- Structured field extraction
- Summary report generation
log_stats
Compute comprehensive log statistics:
- Total and non-empty line counts
- Level distribution with percentages
- Date range coverage
- Unique IP addresses and request counts
- Top user agents
- HTTP status code distribution
- Throughput (entries per second)
Setup
npm install
npm run build
Usage with Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"log-tools": {
"command": "node",
"args": ["path/to/mcp-log-tools/dist/index.js"]
}
}
}
Supported Log Formats
| 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 |
License
MIT
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.