On-Call Compensation Report
The On-Call Compensation Report is an interactive data table that breaks down on-call burden by person — hours scheduled, incidents responded to, off-hours interruptions, and more. Built on the MCP Apps extension, it surfaces the data you need for compensation reviews, load balancing conversations, and team health check-ins, all inside your agent chat session.
What you see
The report opens with a summary row of fleet-wide stats at the top, followed by a sortable table with one row per user.
Summary cards
| Card | What it shows |
|---|---|
| Users On-Call | Total number of users who were on-call in the selected period |
| Total On-Call Hours | Sum of all scheduled on-call hours across all users |
| Incidents Responded | Total incidents, split into high and low urgency |
| Avg Incidents / User | Mean incident count per on-call user |
| Off-Hour Interruptions | Interruptions outside business hours across all users |
| Sleep Interruptions | Interruptions during typical sleep hours across all users |
Compensation table columns
Each column is toggleable — you can show or hide it using the column picker to focus on what matters for your review:
| Column | Description |
|---|---|
| User | Name and team memberships |
| On-Call Hrs | Total hours scheduled on-call during the period |
| Incidents | Total incidents the user was involved in |
| High Urgency | High-urgency incidents assigned to this user |
| Response Hrs | Time engaged in incident response (capped at 24h per incident) |
| Rate /hr | Interruptions per on-call hour — a higher rate means more frequent paging |
| Off-Hr Intrs | Interruptions outside business hours (evenings and early mornings) |
| Sleep Intrs | Interruptions during typical sleep hours (~10pm–8am) |
| BH Intrs | Interruptions during standard business hours |
| Outside BH Hrs | On-call hours outside your configured business hours |
| Weekend Hrs | On-call hours on weekend days |
| Holiday Hrs | On-call hours on configured holidays |
| Max Consec. Hrs | Longest single unbroken stretch of out-of-hours on-call time |
| Unique Periods | Number of distinct out-of-hours windows — high count means frequently interrupted |
What you can do
Set the date range
Use the date pickers at the top to define the reporting window. The table updates immediately when the range changes.
Configure business hours
Click the business hours settings to define what counts as "inside" hours for your team — work days, start/end times, and holidays. The outside-hours columns (Weekend Hrs, Holiday Hrs, Outside BH Hrs, etc.) are all derived from this configuration.
Sort and filter
Click any column header to sort by that metric. Use the search box to filter by user name or team. Use the team dropdown to focus on a single team.
Pick visible columns
Click the column picker to toggle columns on or off. Useful for exporting a focused view to share with managers or HR.
Drill into a user
Click any row to open the user detail modal. It shows the full breakdown for that person — their schedule shifts, incident list, and out-of-hours periods in detail.
How it works
The report calls PagerDuty Analytics tools through the MCP server to fetch on-call schedules and interruption data, then computes the business-hours metrics client-side based on your configuration. It does not write any data to PagerDuty, so --enable-write-tools is not required (though it does not hurt to have it enabled).
Supported clients
| Client | Status |
|---|---|
| VS Code (GitHub Copilot) | Supported |
| Claude Desktop | Supported |
| Goose | Supported |
Try it out
The On-Call Compensation Report is available on the experimental branch:
uvx --from git+https://github.com/PagerDuty/pagerduty-mcp-server@experimental pagerduty-mcp
Or clone and run locally:
git clone -b experimental https://github.com/PagerDuty/pagerduty-mcp-server.git
cd pagerduty-mcp-server
uv run python -m pagerduty_mcp
Then ask your agent:
Show me the on-call compensation report
The On-Call Compensation Report is experimental. It may change or break between commits and is not covered by the standard support policy. Run it in non-production environments.
Feedback
Found a bug or want to request a column? Open a GitHub issue tagged experimental: