Retrieve all services with traces in Jaeger to discover valid service names for further trace analysis.
MIT
347,031 tools. Last updated 2026-07-30 21:55
"Jaeger" matching MCP tools:
- Retrieve the directed call graph of service-to-service dependencies from Jaeger, showing parent-child edges with call counts over a configurable time window.MIT
- Search Jaeger traces by service, operation, tags, time range, and duration. Filter to find specific issues like errors or slow performance.MIT
- Persist a complete agent execution trace including input, output, spans, tool calls, costs, and latency for subsequent evaluation, analysis, or audit.MIT
- Compute latency percentiles and error rates per operation from recent traces to pinpoint slow or failing endpoints.MIT
- Retrieve all operation names traced for a service to use as filters in trace searches. Useful for discovering endpoints or methods before searching for specific traces.MIT
Matching MCP Servers
- Flicense-qualityCmaintenanceRead-only MCP server for querying Jaeger environments from Codex, returning compact, sanitized trace summaries to protect sensitive data.Last updated
- AlicenseAqualityAmaintenanceProvides read-only access to Jaeger distributed tracing data through the Model Context Protocol. Enables Claude and other MCP-capable agents to search traces, inspect spans, and analyze service dependencies directly within conversations.Last updated121MIT
- Structurally compare two Jaeger traces by matching spans on operation and service, revealing added, removed, and changed spans with duration and tag differences.MIT
- Detect performance changes by comparing trace aggregates between two time windows for a service, showing per-operation latency and error rate differences.MIT
- After an incident, combine anomaly history, blast-radius, traces, and log highlights into a single markdown post-mortem report for one service.Apache 2.0
- Identify the critical path and top bottlenecks in a distributed trace to pinpoint performance issues.MIT
- Detect latency and error-rate anomalies in a service by comparing recent traces against a historical baseline to identify performance issues.MIT
- Retrieve complete trace detail including all spans, per-service statistics, and execution tree to analyze performance bottlenecks or identify error origins.MIT
- Analyzes historical trace data to forecast service degradation 2-24 hours ahead, providing confidence levels and recommendations.MIT
- Forecast future throughput demands and resource requirements for a service to enable infrastructure scaling decisions. Provides predictions for the next 7-30 days with confidence intervals.MIT