"Signal" matching MCP servers:

Enables read-only API incident triage through MCP tools that classify HTTP failures, timeouts, slow responses, rate limits, and missing observations, and inspect configured public service endpoints, producing structured and human-readable incident reports.

Connect engineering metrics, DORA performance, deploy risk scoring, and PR health to any AI assistant. Score PRs for deployment risk using a 36-signal model, query team health, incidents, coverage, and more.

Enables AI agents to perform observability analysis across Prometheus-compatible metrics and logs without prior vendor knowledge, including signal discovery, entity topology resolution, root-cause analysis, correlation, and capacity forecasting through natural-language anchors.

Enables evidence-first incident command: investigate outages, analyze evidence, approve simulated responses, verify recovery, and export postmortems through MCP tools.

Enables MCP clients to interactively triage 4G/5G modem logs by summarizing logs, detecting fault signatures with evidence, retrieving relevant troubleshooting knowledge, and generating root-cause reports.

Enables AI assistants to monitor and troubleshoot AWS Application Signals services by tracking service health, analyzing SLO compliance, querying CloudWatch metrics, and investigating issues using distributed tracing with AWS X-Ray.

A Python MCP server that reduces token usage by ~98% when working with log files by auto-detecting format and stripping noise to return only actionable signal.