Discover all services with traces in Jaeger to identify valid service names for tracing queries.
MIT
624,358 tools. Updated 2026-09-30 10:09
"Jaeger" matching MCP tools:
- Lists all operation names Jaeger has recorded for a specific service, enabling discovery of exact operation names to use as filters when searching traces.MIT
- Retrieve the service-to-service dependency graph from Jaeger, including call counts, to map service topology, find high fan-out services, and verify connections.MIT
- Search Jaeger traces by service, operation, tags, and duration to pinpoint errors or slow requests. Returns trace summaries for deeper inspection.MIT
- Find matching Jaeger traces via tag query; supports any tag schema, searches all services concurrently (or a specific one), and sorts results newest-first.MIT
- Compare two Jaeger time windows to detect per-operation regressions, recoveries, and new or removed operations. Results are scored by severity for rapid triage.MIT
Matching MCP Servers
- 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.1541 PyPI2MIT
- FlicenseNot gradedqualityDmaintenanceRead-only MCP server for querying Jaeger environments from Codex, returning compact, sanitized trace summaries to protect sensitive data.-
- Discover all services available in Jaeger and retrieve their names as a JSON list for distributed trace analysis and service discovery.Apache 2.0
- Compare two traces structurally to find added, removed, and changed spans, revealing duration and tag differences.MIT
- Calculate p50/p95/p99 latency and error rate per operation using recent traces, helping pinpoint slow or failing endpoints.MIT
- Compare aggregate trace behavior between two time periods for a service to detect performance changes, such as slower operations or new error patterns.MIT
- Consolidate anomaly history, blast-radius, traces, and log highlights into a single markdown post-mortem report for one service over a time window. Get an incident summary on-call can read in 60 seconds.Apache 2.0
- Analyze a trace to identify its critical path—the longest span chain—and rank spans by self-time to expose the biggest performance bottlenecks.MIT
- Detect latency and error-rate anomalies in a service by comparing recent behavior to a historical baseline, flagging statistically significant deviations that may indicate performance issues.MIT
- Retrieve complete trace details including all spans, per-service stats, and call hierarchy to diagnose slow or failed operations.MIT
- Predict service performance degradation 2-24 hours in advance by analyzing historical trace patterns, critical path trends, and anomaly detection results to enable proactive issue resolution.MIT
- Forecast a service's future throughput and resource needs over 7-30 days, with confidence intervals, to guide infrastructure scaling decisions.MIT
- Aggregate per-operation latency across traces matching tag filters, ranked by total wall time descending to surface latency hotspots.MIT
- Identify the slowest traces for a specific service to diagnose performance bottlenecks. Filter by operation and duration threshold to target problematic requests.Apache 2.0
- Retrieve error traces from Jaeger for a specific service, with optional time range and result limit, including error details.Apache 2.0
- Correlate OpenTelemetry/Jaeger traces with the static call graph to reveal hot production paths and cold code. Pinpoint bottlenecks and dead code from trace JSON files.MIT
- Retrieve latency percentiles and error rates for a service or operation to analyze performance. Filter by time range or specific operation for targeted diagnostics.Apache 2.0