cxone-wfm-intraday-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_intraday_metricsB | List the Intraday metrics available to query, with definitions and units. |
| resolve_intraday_entityB | Resolve a user-friendly name (e.g. 'billing', 'GE') to a canonical queue. |
| get_intraday_snapshotC | Return current Intraday state for all (or selected) queues and the highest-risk queue. |
| get_forecast_vs_actualC | Return per-interval forecast vs actual volume, AHT, and staffing for a queue. |
| get_intraday_risk_driversC | Explain why a queue is at risk: ranked risk drivers with supporting data. |
| get_available_capacityC | Identify queues with spare capacity that could help recover the target queue. |
| simulate_recovery_actionB | Simulate moving N agents from a source queue to a target queue for a duration (minutes). |
| summarise_intraday_recommendationC | Return a plain-English recovery recommendation (what / why / action / impact / trade-offs). |
| load_intraday_dataA | Replace the Intraday dataset with the user's own queues, so every other tool analyzes THEIR data instead of the built-in demo. Each queue object requires: id, name, sla_current, sla_target, volume_forecast, volume_actual, aht_forecast, aht_actual, staffing_planned, staffing_actual (>= 1), occupancy, backlog, risk_status ("at_risk" | "watch" | "healthy"). Optional: aliases (list of strings) and intervals (list of objects with interval, volume_forecast, volume_actual, aht_forecast, aht_actual, staffing_planned, staffing_actual). Percentages are 0-100; times are seconds; staffing is agent counts. Note: this sets the dataset for the whole server process, not per-conversation. Call reset_intraday_data to restore the demo dataset. |
| reset_intraday_dataA | Restore the built-in demo Intraday dataset (undo load_intraday_data). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 10 tools
Each tool has a distinct purpose: snapshot, forecast comparison, risk analysis, capacity query, simulation, recommendation, data loading/reset, entity resolution, metrics listing. No overlapping functionality.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_available_capacity, simulate_recovery_action, reset_intraday_data). No mixing of conventions.
10 tools is well-scoped for a WFM intraday server. Each tool serves a needed function without being excessive or too sparse.
Covers snapshot, forecast comparison, risk analysis, capacity, simulation, recommendation, and data management. Minor gap: no direct tool for updating individual queue attributes, but load_intraday_data allows bulk replacement.