malaria-forecast-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_provincesA | List Angolan provinces under surveillance with their epidemiological stratum. Strata come from K-means clustering of historical burden: 'high', 'moderate' or 'low'. Use this first to resolve province names before calling other tools. |
| get_incidence_historyA | Return weekly malaria incidence history for one province. Args: province: Province name, case-insensitive (e.g. "Luanda", "moxico"). start_week: Optional ISO date (YYYY-MM-DD) lower bound. end_week: Optional ISO date (YYYY-MM-DD) upper bound. max_weeks: Cap on returned rows, most recent first. Defaults to 52. Returns incidence per 1,000 population and the rainfall driver per week. |
| forecast_incidenceA | Forecast weekly malaria incidence 1-8 weeks ahead, with 80% intervals. Args: province: Province name, case-insensitive. horizon_weeks: Forecast horizon, 1 to 8. Horizons beyond the validated range are refused rather than extrapolated. Every point carries an empirical 80% interval derived from rolling-origin
backtest residuals. Read |
| detect_outbreak_signalsA | Flag recent weeks running above the same-calendar-week seasonal baseline. Args: province: Province name, case-insensitive. lookback_weeks: How many recent weeks to screen. Defaults to 12. sigma: Standard deviations above the seasonal baseline required to flag. A flag means "high for this time of year", compared against the same week in prior years -- not merely "high in absolute terms". |
| compare_provincesA | Rank provinces by forecast incidence to support prioritisation. Args: horizon_weeks: Horizon to compare on, 1 to 8. top_n: How many provinces to return, highest forecast first. Use this to answer "where should we pre-position resources", then drill into
a single province with |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| outbreak_briefing | Draft a structured early-warning briefing for a provincial health team. |
| compare_and_prioritise | Rank provinces and justify a resource-allocation recommendation. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| model_card | Provenance, validation method, known limitations and guardrails. |
| provinces_resource | Province directory with epidemiological strata, for grounding context. |
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose: listing provinces, fetching historical incidence, forecasting, detecting outbreak signals, and comparing provinces. No overlap in functionality.
All tool names follow a consistent verb_noun snake_case pattern (list_, get_, forecast_, detect_, compare_).
Five tools perfectly cover the core workflow (list, historical, forecast, detect, compare) without bloat or missing essentials.
The set covers the full forecasting workflow: resolve province names, fetch history, forecast, detect anomalies, and rank provinces for prioritization. No obvious dead ends.