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Let AI query and analyze OpenTelemetry traces to debug apps faster.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "otel-mcp" yet — see the docs or source repo.
Query OpenTelemetry traces for the /checkout endpoint from the last 24 hours. Identify the highest P95 latency trace paths and summarize the slowest spans, likely causes, and optimization suggestions.
A latency analysis highlighting slow trace paths, key bottleneck spans, anomalous patterns, and performance recommendations.
Analyze failed traces for the payment service from the last 2 hours. Cluster them by error type, identify the most common root causes, and show which services and spans they occur in.
A grouped error analysis with the main root causes and the affected services and critical spans.
Use the application's traces to summarize core service dependencies, identify the most frequent cross-service call paths, and point out potential cascading failure risks.
An overview of service dependencies, hot call paths, and potential risk signals for architecture and operations review.
Query and analyze telemetry data in natural language to find performance issues.
Query and analyze Jaeger traces to diagnose service performance and call issues.
Connect AI coding assistants to OpenTelemetry docs, examples, and instrumentation guidance.
Track AI usage, costs, logs, and debug model interactions across apps.
Query Jaeger traces, services, and operations using natural language.
Use AI to search Datadog logs, traces, metrics, and correlate incidents.