A
licenseNot graded
qualityB
maintenanceEnables coding agents to access live runtime observability data such as logs, deploys, and health metrics for evidence-based incident triage.
1
MIT
Production Monitoring MCP
by kowshik3383
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TDQS
A3.6/5.0
Scored across 14 tools
Disambiguation4/5
Most tools target distinct resource+action pairs (Sentry errors vs deployments vs uptime vs latency), and descriptions clarify boundaries. Slight overlap between get_production_health and get_observability_status (a pulse vs provider/credential status), and correlate_incident/explain_incident form a related triage/briefing pair, but each remains differentiable.
Naming Consistency5/5
All 14 tools use snake_case with a consistent verb_noun pattern (get_recent_errors, check_uptime, analyze_logs, compare_deployments, explain_incident). No mixing of camelCase or vague bare verbs.
Tool Count5/5
14 tools is well within the ideal 3-15 range and each earns its place across distinct monitoring and incident-response stages. No redundant or filler tools.
Completeness5/5
The surface covers the full incident lifecycle: detection (health, errors, uptime, latency), investigation (error details, deployment logs, commit details, regressions), correlation (correlate_incident), and reporting (explain_incident). No obvious dead ends for the stated production monitoring purpose.
Maintenance
ActivityMaintained
ResponsivenessNo issues