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。
Deploy status across all projects. Shows ECS service versions, Vercel deployments, recent deploys, pending deploys, and CI/CD pipeline state.
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。
Before executing, load available context:
Preferences: Read ${CLAUDE_PLUGIN_DATA_DIR:-$HOME/.claude/plugins/data/ops-ops-marketplace}/preferences.json
timezone — display all deploy timestamps in the correct timezoneDaemon health: Read ${CLAUDE_PLUGIN_DATA_DIR}/daemon-health.json
infra-monitor status — if not running, note that ECS data may be staleSecrets: AWS and Vercel credentials required.
$AWS_PROFILE / $AWS_ACCESS_KEY_ID → doppler secrets get AWS_ACCESS_KEY_ID --plain → vault query cmd from prefs$VERCEL_TOKEN → doppler secrets get VERCEL_TOKEN --plain → vault| Command | Usage | Output |
|---|---|---|
aws ecs list-clusters --output json | All ECS clusters | {clusterArns: [...]} |
aws ecs list-services --cluster <name> --output json | Services in cluster | {serviceArns: [...]} |
aws ecs describe-services --cluster <name> --services <arn> --output json | Service health | {services: [{serviceName, status, runningCount, desiredCount, pendingCount}]} |
aws logs tail /ecs/<service> --since 1h --format short | ECS logs | Log lines |
| Command | Usage | Output |
|---|---|---|
gh run list --repo <owner/repo> --limit 5 --json status,conclusion,name,headBranch,createdAt,databaseId | CI runs | JSON array |
gh run view <id> --repo <repo> --log-failed | Failed CI logs | Log output |
gh run watch <run-id> --repo <repo> | Stream CI run | Live output (use with Monitor) |
If CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set, use Agent Teams when checking deploy platforms in parallel. This enables:
Team setup (only when flag is enabled):
TeamCreate("deploy-team")
Agent(team_name="deploy-team", name="ecs-checker", prompt="List all ECS clusters and describe service health, running/desired counts")
Agent(team_name="deploy-team", name="vercel-checker", prompt="List Vercel projects and recent deployments with status")
Agent(team_name="deploy-team", name="ci-checker", prompt="Check GitHub Actions runs across all registered repos for failures")
If the flag is NOT set, use standard fire-and-forget subagents.
${CLAUDE_PLUGIN_ROOT}/bin/ops-infra 2>/dev/null || \
aws ecs list-clusters --output json 2>/dev/null
for cluster in $(aws ecs list-clusters --output json 2>/dev/null | jq -r '.clusterArns[]'); do
cluster_name=$(basename "$cluster")
aws ecs list-services --cluster "$cluster_name" --output json 2>/dev/null | \
jq -r '.serviceArns[]' | while read svc; do
aws ecs describe-services --cluster "$cluster_name" --services "$svc" \
--output json 2>/dev/null | jq '.services[] | {name: .serviceName, desired: .desiredCount, running: .runningCount, pending: .pendingCount, image: (.taskDefinition // "unknown"), status: .status}'
done
done
REGISTRY="${CLAUDE_PLUGIN_ROOT}/scripts/registry.json"
[ -f "$REGISTRY" ] || REGISTRY="${CLAUDE_PLUGIN_ROOT}/scripts/registry.example.json"
for repo in $(jq -r '.projects[] | select(.gsd == true) | .repos[]' "$REGISTRY" 2>/dev/null); do
echo "=== $repo ==="
gh run list --repo "$repo" --limit 5 --json status,conclusion,name,headBranch,createdAt,databaseId 2>/dev/null
done
Use mcp__claude_ai_Vercel__list_projects then mcp__claude_ai_Vercel__list_deployments for each project (limit 5 per project).
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
OPS ► DEPLOY STATUS — [timestamp]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
ECS SERVICES
CLUSTER SERVICE D/R/P STATUS LAST DEPLOY
─────────────────────────────────────────────────────
[cluster] [service] [x/x/x] ACTIVE [time ago]
...
VERCEL DEPLOYMENTS
PROJECT ENV STATUS COMMIT DEPLOYED
─────────────────────────────────────────────────────
[project] production READY [sha] [time ago]
...
CI/CD PIPELINE
REPO BRANCH WORKFLOW STATUS AGE
─────────────────────────────────────────────────────
example-api main Deploy API ✓ success 2h
example-web dev Build ✗ failure 1h
...
PENDING DEPLOYS (branch ready, not yet deployed)
[repo] [branch] [PR#] [CI status] → needs merge to trigger
──────────────────────────────────────────────────────
After rendering, use batched AskUserQuestion calls (max 4 options each). Only show actions relevant to the current state (e.g., skip "View logs for failing service" if nothing is failing). If <=4 relevant actions, use a single call. If >4, batch:
AskUserQuestion call 1:
[View logs for [failing service]]
[Trigger manual deploy for [project]]
[View build logs for [failing CI run]]
[More actions...]
AskUserQuestion call 2 (only if "More actions..."):
[Check Vercel [project] runtime logs]
[Open GitHub Actions for [repo]]
[Back to dashboard]
If $ARGUMENTS has a project alias, show only that project's deploy info + last 10 CI runs + option to view logs.
For failing deploys: offer to view logs via mcp__claude_ai_Vercel__get_deployment_build_logs or ECS CloudWatch logs.
If user selects manual deploy (option b), confirm with AskUserQuestion before triggering:
Trigger deploy for [project]:
Environment: [production/staging]
Branch: [branch]
Last commit: [sha] — [message]
[Deploy now] [View diff since last deploy first] [Cancel]
If user selects to view logs, show the logs and use AskUserQuestion:
[Dispatch fix agent for this failure] [Redeploy] [Back to dashboard]
When watching a deploy in progress, use Monitor to stream logs:
Monitor(command: "gh run watch <run-id> --repo <repo>")
For ECS deploys: Monitor(command: "aws ecs wait services-stable --cluster <cluster> --services <service>")
Use TaskCreate per project being deployed. Update with TaskUpdate as deploys succeed/fail.
When Vercel MCP tools are unavailable, use WebFetch with the Vercel API directly:
WebFetch(url: "https://api.vercel.com/v6/deployments?projectId=<id>&limit=5", headers: {"Authorization": "Bearer $VERCEL_TOKEN"})
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。