npm:portkey-admin-mcp

Get cost time-series data with summary.total_cost, summary.average_cost_per_request, and per-bucket total/avg cost. Use this for spend analysis and sp

Get request-volume time-series data with summary.total_requests, summary.successful_requests, summary.failed_requests, and per-bucket total/success/fa

Get token-usage time-series data with summary.total_tokens, summary.prompt_tokens, summary.completion_tokens, and per-bucket total/prompt/completion c

Get latency time-series data with summary.avg_latency_ms, summary.p50_latency_ms, summary.p90_latency_ms, summary.p99_latency_ms, and per-bucket laten

Get error-count time-series data with summary.total_errors and per-bucket counts. Use this for high-level error trends; use get_error_rate_analytics f

Get error-rate time-series data with summary.error_rate_percent and per-bucket percentages of total requests. Use this for reliability and SLA trends;

Get cache-hit-only latency time-series data with summary.total_latency, summary.avg_latency, and per-bucket total/avg latency. Use this to evaluate ca

Get cache-effectiveness time-series data with summary.hit_rate, summary.total_hits, summary.total_misses, and per-bucket hits/misses/rate. Use this to

Get user-growth time-series data with summary.total_active_users, summary.total_new_users, and per-bucket active/new user counts. Use this for growth

Get stacked error-series data grouped by HTTP status code over time, with summary and per-code series. Use this to see which error classes dominate; u

Get HTTP error-code distribution time-series data with summary and per-code series. Use this to see which codes occur most often; use get_error_stacks

Get per-user request-count time-series data with counts grouped by user. Use this to find heavy users and traffic concentration; use get_users_analyti

Get rescued-request time-series data showing requests recovered by retry or fallback handling. Use this only when your configs include resilience feat

Get feedback-submission time-series data with summary totals and per-bucket counts. Use this as the top-level feedback trend view; use get_feedback_mo

Get feedback time-series data grouped by model, with per-model counts over time. Use this to compare feedback volume and satisfaction across models; u

Get raw feedback-score distribution time-series data with per-score buckets. Use this to understand sentiment mix; use get_feedback_weighted_analytics

Get weighted feedback-score time-series data using the weight recorded at feedback creation. Use this for calibrated quality metrics; use get_feedback

Get a paginated per-user breakdown with total_groups, group_count, and a users array containing request count, cost, and token usage. Use this for bil