A
licenseA
qualityA
maintenanceMCP server exposing AI agent observability tools: list, inspect, and deterministically replay recorded agent execution traces for debugging failures.
1
52 PyPI
Apache 2.0
MCP Trace Inspector
by abhishekash
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TDQS
A3.5/5.0
Scored across 12 tools
Disambiguation4/5
Most tools have distinct analytical purposes (failure_report, tool_stats, security_audit, span_tree, slowest_spans, etc.), but token_usage and compare_runs overlap in cost/token/latency aggregation, and recent_activity vs list_runs both surface recent runs/spans, which could cause occasional misselection.
Naming Consistency5/5
All 12 tools use a consistent snake_case noun_phrase or verb_noun pattern (failure_report, tool_stats, list_runs, run_summary, span_tree), making names predictable and readable.
Tool Count5/5
12 tools is well within the ideal 3-15 range and each targets a specific diagnostic need (failures, stats, security, activity, comparison, runs, summary, tree, latency, approvals, tokens, search).
Completeness4/5
The surface covers run listing, summaries, span trees, failures, latency, tokens, security, approvals, search, and comparison—strong lifecycle coverage for trace inspection. Minor gaps like deleting/exporting traces or filtering by date/tool in list_runs are workaround-able but not critical.
Maintenance
ActivityMaintained
ResponsivenessNo issues