Log Detective MCP
OfficialRelated Servers
Alternatives to Log Detective MCP
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityAmaintenanceEnables AI agents to analyze, cluster, compare, and export reports from local log files through seven read-only tools, returning compact evidence packs with line-number citations instead of raw log dumps. All processing happens on the local machine, so log data never leaves the environment.854 PyPI1MIT
- AlicenseNot gradedqualityBmaintenanceEnables LLMs to analyze logs by extracting patterns, redacting secrets, and providing token-efficient summaries from files, Docker containers, or journald.5MIT
- FlicenseNot gradedqualityDmaintenanceCompresses log files into templates and statistics using Drain3, and exposes them to AI assistants via an MCP server for efficient log monitoring and anomaly detection.-
- AlicenseAqualityCmaintenanceMCP server that wraps Drain3 for streaming log template mining, read-only matching, parameter extraction, and model persistence, exposing tools and resources to train on logs and query learned templates.8MIT
- FlicenseBqualityDmaintenanceProvides tools to analyze test failures, cluster similar failures, and detect flaky tests from input or log files, helping QA teams debug and triage issues.3-
- AlicenseAqualityDmaintenanceSemantic log clustering for incident triage, exposed as an MCP server.1Academic Free v1.1
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one extracts representative log snippets via clustering, while the other extracts Python tracebacks. Shared input parameters do not create ambiguity because their outputs and targeting heuristics are different.
Both tools follow the same predictable verb_noun snake_case pattern: extract_log_snippets and extract_python_tracebacks. There is no mixing of conventions or vague verbs.
Two tools is on the thin side for a server called Log Detective MCP, even though each tool is focused. It is borderline rather than clearly well-scoped for broader log analysis.
The surface covers two specific extraction modes but lacks general log search, filtering, aggregation, or traceback support for other languages. These are notable gaps for a log-detection toolset, though the provided tools can handle some initial investigation.