Audit the configured MCP servers (user + project scope) via the Agent Monitor Config Explorer API: transport (stdio vs http), command/args and env variable names, headers, and the source file each definition came from. Reads /api/cc-config/mcp. Use when reviewing MCP integrations for hygiene, duplication, or unexpected transports.
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실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Inventory and audit every Model Context Protocol server the user has
configured — both user-scope and project-scope — read through the Agent Monitor
dashboard at http://localhost:4820.
The user provides: $ARGUMENTS
This may be:
| Endpoint | Returns |
|---|---|
GET /api/cc-config/mcp | { user:[…], projectScoped:[…] }. Each server: { name, source, kind } where kind is stdio (with command, args, envNames), http (with url, headers), or unknown. source names the file the definition came from (e.g. ~/.claude.json (top-level), ~/.claude.json (projects[<root>]), ~/.claude/settings.json) |
List every server from user and projectScoped. For each show name,
source, kind, and the transport detail:
command, its args, and the envNames (names only — values
are not exposed by the API).url and the headers key names (values not exposed).Separate user-scope from project-scope servers. Flag any name that appears in
both scopes (project may shadow user) and any duplicate definitions across
source files.
kind: "unknown" (malformed or
unsupported definition).envNames; note they depend on
environment variables being present at launch.url host so the user can
confirm they trust the remote.Scope | Name | Kind | Transport detail | Source).source.http://localhost:4820, say so and tell
the user to start it with npm start from the repo root.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Inspect fired CCAM alerts and manage alert rules for token thresholds, event patterns, inactivity, and status duration. Use when acknowledging alerts, creating or editing a rule, checking cooldowns, or connecting alert rules to webhook targets.
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Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error propagation anomalies), and sessions with abnormal metadata (extreme turn_count, high thinking_blocks, zero turn_duration).
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Produce a detailed report on APIError events from Agent Monitor data — counts over time, which sessions and models are affected, and the likely root cause (rate limits, overload/529, or context-window pressure) inferred from each event's summary and data payload. Use when API errors spike or when you need to explain why requests are failing.
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Benchmark one session (or a small recent set) against the rolling average using Agent Monitor data — cost, total tokens, tool count, and workflow complexity score — and report where each metric lands as a percentile of the population. Tells you whether a session was normal, cheap, or an outlier. Use when judging whether a session was typical or out of band.
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Define a spend budget for Claude Code and, optionally, create a cost alert rule that fires when usage crosses the limit, via POST /api/alerts/rules on the Agent Monitor dashboard. Reads current spend from /api/pricing/cost to size the budget sensibly and explains every rule field before writing. Use when setting a spend limit or wiring up a budget guardrail.
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Analyze prompt-cache effectiveness for Claude Code usage from the Agent Monitor dashboard — cache hit rate (total_cache_read / (total_cache_read + total_input)), cache_write vs cache_read reuse, cache-read vs cache-write spend, and the sessions with the poorest reuse. Pulls token totals from /api/analytics, per-session detail from /api/sessions, and dollar splits from /api/pricing/cost. Use when diagnosing cache spend or deciding whether prompt caching is paying off.
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