Log
Exposes five log analysis tools to Claude via MCP: parse_logs handles JSON, Apache/Nginx, syslog, and custom regex patterns with named capture groups. filter_logs lets you query by level, date range, keywords, or regex. analyze_logs surfaces the top 10 normalized errors, hourly error rates, request volume, slow endpoints, and anomaly detection using standard deviation. format_logs converts between JSON, plain text, CSV, and colorized table output. log_stats computes distributions, unique IPs, user agents, status codes, and throughput. Reach for this when you need Claude to investigate application logs, identify patterns in access logs, or generate operational reports without writing throwaway scripts.
- GitHub stars
- 1
- tools
- 5
- transport
- STDIO
- last updated
- Mar 22, 2026
Tools
5 toolsPublic tool metadata for what this MCP can expose to an agent.
parse_logsParse 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.
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.
No parameter schema in public metadata yet.
filter_logsFilter parsed log entries by log level, date range, keyword search, regex pattern matching, and source/logger name. Returns matched entries along with level occurrence counts.
Filter parsed log entries by log level, date range, keyword search, regex pattern matching, and source/logger name. Returns matched entries along with level occurrence counts.
No parameter schema in public metadata yet.
analyze_logsAnalyze log patterns to surface operational insights: top frequent errors, error rate over time, request volume per hour, slowest endpoints, and anomaly detection.
Analyze log patterns to surface operational insights: top frequent errors, error rate over time, request volume per hour, slowest endpoints, and anomaly detection.
No parameter schema in public metadata yet.
format_logsConvert between log formats and produce reports, including JSON to plain text, CSV, or table conversion, ANSI colorization by log level, structured field extraction, and summary report generation.
Convert between log formats and produce reports, including JSON to plain text, CSV, or table conversion, ANSI colorization by log level, structured field extraction, and summary report generation.
No parameter schema in public metadata yet.
log_statsCompute comprehensive log statistics including line counts, level distribution, date range coverage, unique IP addresses and request counts, top user agents, HTTP status code distribution, and throughput.
Compute comprehensive log statistics including line counts, level distribution, date range coverage, unique IP addresses and request counts, top user agents, HTTP status code distribution, and throughput.
No parameter schema in public metadata yet.
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@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
Details
- Repository
- github.com/rog0x/mcp-log-tools
- Category
- Monitoring & Observability
- Package
@rog0x/mcp-log-tools- Transport
- STDIO
- Registry
- MCP registry, active
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