get_automation_analytics
Retrieve analytics and performance data for workflow automations to monitor efficiency, track metrics, and optimize processes using time-based filtering.
Instructions
Get analytics and performance data for workflow automations
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | No | Project ID to filter analytics (optional) | |
| time_range | No | Time range for analytics | week |
| include_inactive | No | Include disabled automations in analytics |
Implementation Reference
- src/tools/workflow-automation.ts:377-409 (handler)Main execution handler for the get_automation_analytics tool. Parses input, fetches rules and executions from Supabase, computes analytics using helper, and returns structured performance data.export const getAutomationAnalytics = requireAuth(async (args: any) => { const { project_id, time_range, include_inactive } = GetAutomationAnalyticsSchema.parse(args) logger.info('Getting automation analytics', { project_id, time_range }) const [rules, executions] = await Promise.all([ supabaseService.getWorkflowRules({ project_id, enabled: include_inactive ? undefined : true }), supabaseService.getWorkflowExecutions({ project_id, time_range }) ]) // Calculate analytics const analytics = calculateAutomationAnalytics(rules, executions, time_range) return { summary: { total_rules: rules.length, active_rules: rules.filter(r => r.enabled).length, total_executions: executions.length, successful_executions: executions.filter(e => e.success).length, time_range }, performance: analytics.performance, top_performers: analytics.topPerformers, failure_analysis: analytics.failureAnalysis, recommendations: analytics.recommendations } })
- Zod schema for validating input parameters: project_id (optional), time_range (enum with default 'week'), include_inactive (boolean default false).const GetAutomationAnalyticsSchema = z.object({ project_id: z.string().optional(), time_range: z.enum(['day', 'week', 'month', 'quarter']).default('week'), include_inactive: z.boolean().default(false) })
- src/tools/workflow-automation.ts:346-369 (registration)MCPTool registration object defining name, description, and input schema for the tool.export const getAutomationAnalyticsTool: MCPTool = { name: 'get_automation_analytics', description: 'Get analytics and performance data for workflow automations', inputSchema: { type: 'object', properties: { project_id: { type: 'string', description: 'Project ID to filter analytics (optional)' }, time_range: { type: 'string', enum: ['day', 'week', 'month', 'quarter'], default: 'week', description: 'Time range for analytics' }, include_inactive: { type: 'boolean', default: false, description: 'Include disabled automations in analytics' } } } }
- src/tools/workflow-automation.ts:602-608 (registration)Export mapping tool names to their handler functions, registering get_automation_analytics to getAutomationAnalytics.export const workflowAutomationHandlers = { create_workflow_rule: createWorkflowRule, list_workflow_rules: listWorkflowRules, execute_workflow_rule: executeWorkflowRule, create_trigger_automation: createTriggerAutomation, get_automation_analytics: getAutomationAnalytics }
- Key helper function called by the handler to compute detailed analytics including performance metrics, top performers, failure analysis, and recommendations.function calculateAutomationAnalytics(rules: any[], executions: any[], timeRange: string): any { const now = new Date() const timeRangeMs = getTimeRangeMs(timeRange) const recentExecutions = executions.filter(e => new Date(e.executed_at).getTime() > now.getTime() - timeRangeMs ) // Performance metrics const performance = { total_executions: recentExecutions.length, success_rate: recentExecutions.length > 0 ? (recentExecutions.filter(e => e.success).length / recentExecutions.length) * 100 : 0, average_execution_time: calculateAverageExecutionTime(recentExecutions), executions_per_day: recentExecutions.length / getDaysInRange(timeRange) } // Top performing rules const rulePerformance = new Map() recentExecutions.forEach(exec => { const ruleId = exec.rule_id if (!rulePerformance.has(ruleId)) { rulePerformance.set(ruleId, { executions: 0, successes: 0 }) } const stats = rulePerformance.get(ruleId) stats.executions++ if (exec.success) stats.successes++ }) const topPerformers = Array.from(rulePerformance.entries()) .map(([ruleId, stats]) => ({ rule_id: ruleId, rule_name: rules.find(r => r.id === ruleId)?.name || 'Unknown', executions: stats.executions, success_rate: (stats.successes / stats.executions) * 100 })) .sort((a, b) => b.executions - a.executions) .slice(0, 5) // Failure analysis const failures = recentExecutions.filter(e => !e.success) const failureReasons = new Map() failures.forEach(f => { const reason = f.error_message || 'Unknown error' failureReasons.set(reason, (failureReasons.get(reason) || 0) + 1) }) const failureAnalysis = { total_failures: failures.length, failure_rate: recentExecutions.length > 0 ? (failures.length / recentExecutions.length) * 100 : 0, common_failures: Array.from(failureReasons.entries()) .map(([reason, count]) => ({ reason, count })) .sort((a, b) => b.count - a.count) .slice(0, 3) } // Recommendations const recommendations = generateAutomationRecommendations(performance, failureAnalysis, rules) return { performance, topPerformers, failureAnalysis, recommendations } }