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# How obs-mcp boosts AI-native OpenShift observability

**[Red Hat Developer](https://daily.dev/sources/rhdev)** · 7 min read · 0 upvotes · 0 comments

## Summary

obs-mcp is a Go-native MCP server component integrated into the MCP server for Red Hat OpenShift that bridges AI agents with cloud-native observability backends including Prometheus, Thanos, Grafana Loki, Grafana Tempo, and OpenTelemetry Collectors. It addresses the 'manual correlation bottleneck' in incident response by letting LLMs query metrics (PromQL), traces (TraceQL), and logs (LogQL) through natural language. Key design principles include a discovery-first model (requiring list_metrics before querying), strict cardinality guardrails via Thanos TSDB status endpoints, adaptive toolset scoping via --toolsets flag, and stateless horizontal scalability. The goal is to reduce MTTR by automating signal correlation, democratize complex query languages for non-experts, and enable AI agents to behave like experienced SREs during incident triage.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://developers.redhat.com/articles/2026/07/16/how-obs-mcp-boosts-ai-native-openshift-observability>

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---

Tags: [#kubernetes](https://daily.dev/tags/kubernetes), [#golang](https://daily.dev/tags/golang), [#observability](https://daily.dev/tags/observability), [#mcp](https://daily.dev/tags/mcp), [#openshift](https://daily.dev/tags/openshift)

[View this post on daily.dev](https://daily.dev/posts/how-obs-mcp-boosts-ai-native-openshift-observability-ohkjtp3ml)

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