SRE Log Intelligence HTTP
Exposes HTTP endpoints for SRE log intelligence, supporting log querying, pattern matching, and insight extraction from production system logs. SRE engineers and DevOps teams use it to investigate incidents, monitor reliability metrics, and correlate events across distributed systems.
Overview
SRE Log Intelligence HTTP is an MCP server providing HTTP-based access to log analysis functions optimized for Site Reliability Engineering (SRE). It processes structured and unstructured logs from infrastructure, applications, and services, delivering actionable intelligence for maintaining high availability and performance.
Key Capabilities
- HTTP API for submitting log queries to retrieve events based on time ranges, filters, and keywords.
- Log aggregation and parsing to normalize data from multiple sources like Kubernetes, cloud providers, or custom stacks.
- Basic anomaly detection and aggregation for metrics like error rates and latency spikes.
No additional specific tools are listed, focusing on core HTTP interactions for log intelligence workflows.
Use Cases
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During on-call incident response, query logs (log_query) to filter errors by service and timestamp, identifying root causes in seconds.
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For post-mortem analysis, aggregate logs over a week to compute SLO violation trends and failure patterns.
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In capacity planning, extract throughput and error metrics from logs to forecast scaling needs.
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Real-time monitoring setups where HTTP calls trigger alerts on detected anomalies in access or application logs.
Who This Is For
- SRE engineers managing production reliability.
- DevOps teams automating log-based alerting and dashboards.
- Operations analysts reviewing logs for performance bottlenecks.
This server suits environments with high-volume logging needs, integrating into CI/CD pipelines or monitoring tools via simple HTTP requests.