Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Unified APM and monitoring surface. Polls Datadog, New Relic, and OpenTelemetry backends for active alerts, error traces, and entity health. Use --watch for live polling every 60 seconds. Use --setup to configure monitoring credentials.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
PREFS="${CLAUDE_PLUGIN_DATA_DIR:-$HOME/.claude/plugins/data/ops-ops-marketplace}/preferences.json"
DD_API_KEY=$(jq -r '.datadog_api_key // empty' "$PREFS" 2>/dev/null)
NR_API_KEY=$(jq -r '.newrelic_api_key // empty' "$PREFS" 2>/dev/null)
OTEL_ENDPOINT=$(jq -r '.otel_endpoint // empty' "$PREFS" 2>/dev/null)
Determine $ARGUMENTS mode:
--setup → run Setup flow--watch → run Watch mode--setup)Ask which backends to configure:
Which monitoring backends would you like to configure?
[Datadog] [New Relic] [OpenTelemetry] [All three]
For each selected backend, collect credentials via AskUserQuestion free-text input (one at a time, ≤4 options per call):
Datadog:
datadog_api_key — API Key from app.datadoghq.com/organization-settings/api-keysdatadog_app_key — Application Key from app.datadoghq.com/organization-settings/application-keysNew Relic:
newrelic_api_key — User API Key from one.newrelic.com/api-keysnewrelic_account_id — Numeric Account ID from New Relic admin portalOpenTelemetry:
otel_endpoint — Base URL of your OTEL-compatible backend (e.g., https://otlp.grafana.net)Write each credential to preferences.json using atomic tmpfile swap:
tmp=$(mktemp)
jq --arg k "$KEY" --arg v "$VALUE" '.[$k] = $v' "$PREFS" > "$tmp" && mv "$tmp" "$PREFS"
Run smoke test after saving:
curl -sf -H "DD-API-KEY: $DD_API_KEY" -H "DD-APPLICATION-KEY: $DD_APP_KEY" "https://api.datadoghq.com/api/v1/validate" → expect {"valid": true}curl -sf -H "Api-Key: $NR_API_KEY" "https://api.newrelic.com/graphql" -d '{"query":"{ actor { user { name } } }"}' → expect data.actor.usercurl -sf "$OTEL_ENDPOINT/healthz" → expect HTTP 200Report ✅ or ❌ with status for each backend.
If CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set, use Agent Teams when querying multiple backends simultaneously. This enables:
Team setup (only when flag is enabled, multiple backends configured):
TeamCreate("monitor-probes")
Agent(team_name="monitor-probes", name="datadog-probe", subagent_type="ops:monitor-agent", ...)
Agent(team_name="monitor-probes", name="newrelic-probe", subagent_type="ops:monitor-agent", ...)
Agent(team_name="monitor-probes", name="otel-probe", subagent_type="ops:monitor-agent", ...)
If the flag is NOT set or only one backend is configured, use a single monitor-agent subagent.
Spawn monitor-agent via the Agent tool. Display the result as a formatted dashboard:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
OPS ► MONITOR [<timestamp>]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DATADOG ✅ healthy (0 alerts)
NEW RELIC 🔴 2 critical entities
OTEL ✅ healthy
──────────────────────────────────────────────────────
Total alerts: 2 Severity: CRITICAL
Status icons:
✅ — healthy (0 alerts / configured and reachable)⚠️ — warning (warn-level alerts present)🔴 — critical (critical alerts or unreachable)⬜ — not configuredFor each alert or critical entity, display: service name, alert name, and link to the relevant dashboard.
If no backends are configured, show a setup prompt:
No monitoring backends configured. Run /ops:monitor --setup to add Datadog, New Relic, or OTEL.
--watch)Poll every 60 seconds. On each tick:
while true; do
RESULT=$(# spawn monitor-agent and capture JSON output)
# Diff against previous tick
# Print: timestamp, changed items only
# 🆕 new alert: <name>
# ✅ resolved: <name>
sleep 60
done
Exit on Ctrl-C.
--backend filterIf --backend datadog|newrelic|otel is specified, query and display only that backend.
| Backend | Auth header | Base URL | Health endpoint |
|---|---|---|---|
| Datadog | DD-API-KEY: $key + DD-APPLICATION-KEY: $app_key | https://api.datadoghq.com | /api/v1/validate |
| New Relic | Api-Key: $key | https://api.newrelic.com/graphql | POST GraphQL query |
| OTEL | varies by backend | $OTEL_ENDPOINT | /healthz |
# Datadog — active alerts
curl -sf \
-H "DD-API-KEY: ${DD_API_KEY}" \
-H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \
"https://api.datadoghq.com/api/v1/monitor?monitor_tags=*&with_downtimes=false" \
| jq '[.[] | select(.overall_state == "Alert" or .overall_state == "Warn")]'
# New Relic — critical entities (GraphQL)
curl -sf \
-H "Api-Key: ${NR_API_KEY}" \
-H "Content-Type: application/json" \
-d '{"query":"{ actor { entitySearch(queryBuilder: {alertSeverity: CRITICAL}) { results { entities { name alertSeverity entityType } } } } }"}' \
"https://api.newrelic.com/graphql"
# OTEL — health check
curl -sf "${OTEL_ENDPOINT}/healthz"
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
日本語の概要は準備中です。原文の説明を表示しています。
Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
日本語の概要は準備中です。原文の説明を表示しています。
Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
日本語の概要は準備中です。原文の説明を表示しています。
Audit whether a website can be found, crawled, and cited by AI answer engines such as ChatGPT Search, Perplexity, Google AI Overviews, and Microsoft Copilot. Use when someone asks why their brand is missing from AI answers, whether AI crawlers can read their site, how to get cited by ChatGPT or Perplexity, or asks for a GEO or AEO (generative / answer engine optimization) review. Produces a citation baseline across buyer-intent prompts, a crawler-access check, a citability review of named pages, and a ranked fix list. Not for keyword rank tracking, paid search, or pages behind a login.
日本語の概要は準備中です。原文の説明を表示しています。
Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。