Pagerly MCP

SlackとMicrosoft Teams向けのオンコールおよびインシデント管理：オンコール担当者の確認、ローテーションとオーバーライドの管理、インシデントの宣言と更新、AIによるインシデント調査の実行、アラートノイズの分析が可能です。

pagerly.io で表示このMCPを試すスポンサー

ドキュメント

For the complete documentation index, see llms.txt. Markdown versions of documentation pages are available by appending .md to page URLs; this page is available as Markdown.

Remote MCP Server

Connect AI assistants like Claude (Desktop & Code CLI), Cursor, ChatGPT, and automated AI coding agents directly to Pagerly using the Model Context Protocol (MCP).

⚡ Overview

The Pagerly Remote MCP Server exposes your on-call schedules, incident management, SRE AI investigations, MTTR metrics, alert noise analytics, and Status Pages directly to your local or cloud AI tools.

  • Server Endpoint: https://api.pagerly.io/mcp
  • Protocol: JSON-RPC 2.0 over HTTP / SSE
  • Authentication: OAuth 2.0 (Browser Login) or API Key (Authorization: Bearer <token>)

🛠️ Available MCP Tools

1. pagerly_get_oncall

Query who is currently on call for any team or rotation schedule across PagerDuty, Opsgenie, Datadog, Google Calendar, and Outlook.

{
  "org_id": "T0123456",
  "team_name": "Platform"
}

2. pagerly_create_incident

Declare a new incident, provision a dedicated Slack channel, assign severity (P1-P4), and set the incident commander.

{
  "org_id": "T0123456",
  "title": "High Latency on Payment Gateway",
  "severity": "P1",
  "service_id": "payments-service"
}

3. pagerly_update_incident

Update ongoing incident status (Open, In Progress, Investigating, Identified, Monitoring, Resolved) or severity.

{
  "org_id": "T0123456",
  "incident_id": "INC-102",
  "status": "Resolved"
}

4. pagerly_get_ai_investigation

Fetch or trigger a deep SRE AI investigation for an incident. Returns:

  • Telemetry: Datadog / CloudWatch Metrics (-15m) & Error Logs (300 lines)
  • Deployments: Recent GitHub deploy events (-2h)
  • Root Cause Hypotheses & Debugging Next Steps
{
  "org_id": "T0123456",
  "incident_id": "INC-102",
  "run_new": true
}

5. pagerly_incident_stats

Query incident analytics, Mean Time to Resolve (MTTR), severity distribution, and recurring root-cause hypothesis themes.

{
  "org_id": "T0123456",
  "days": 30
}

6. pagerly_alert_noise_analysis

Analyze alert volume vs actual incidents, noise ratio %, top noisy alert sources (CloudWatch, Datadog, etc.), and off-hours page percentages.

{
  "org_id": "T0123456",
  "days": 30
}

7. pagerly_update_statuspage

Update component health (Operational, Degraded Performance, Partial Outage, Major Outage) or publish public status updates.

{
  "org_id": "T0123456",
  "component_name": "API Gateway",
  "status": "Degraded Performance",
  "incident_message": "Investigating elevated error rates."
}

8. pagerly_update_schedule

Update team rotation schedule ID, rotation frequency (daily, weekly), or timezone settings.

{
  "org_id": "T0123456",
  "team_name": "Platform",
  "rotation_frequency": "weekly",
  "timezone": "America/New_York"
}

9. pagerly_set_reminder

Set or update shift rotation reminder notifications for an on-call team.

{
  "org_id": "T0123456",
  "team_name": "Platform",
  "reminder_time": "1day"
}

🔑 Quick Setup

1. Claude Code CLI

Add the server via CLI:

claude mcp add pagerly --transport http https://api.pagerly.io/mcp

2. Claude Desktop & Cursor

Add to your claude_desktop_config.json or Cursor MCP settings:

3. Claude.ai Custom Connectors (Enterprise)

If Claude prompts for manual OAuth settings in custom connector options:

  • Server URL: https://api.pagerly.io/mcp
  • Authorization URL: https://workspace.pagerly.io/oauth/authorize
  • Token URL: https://workspace.pagerly.io/oauth/token
  • OAuth Client ID: pagerly_mcp_client (or auto-registered via .well-known discovery) Upon first query, Claude will prompt you to authenticate via OAuth browser login.