DMAP-AI MCP Server

Drought Monitoring and Analysis Platform — Model Context Protocol Server

DMAP-AI is a remote MCP server by AgriMetSoft LLC that exposes drought monitoring and analysis tools to AI assistants — including Claude, ChatGPT, and any MCP-compatible client. It provides SPI tables, drought severity event detection, wavelet scalogram analysis, and drought periodicity diagnostics over real climate data (NASA POWER and ERA5).

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Quick Connect

Claude (claude.ai)

1. Go to Settings → Connectors → Add custom connector
2. Name: DMAP-AI
3. URL: https://droughtanalysis.com/mcp
4. Click Add, then enable it in your chat via the + button

ChatGPT / Gemini

DMAP-AI may also be available through compatible AI apps or custom assistant workflows. MCP support depends on the client’s current connector features.

Any MCP client (mcp.json / config)

{
  "mcpServers": {
    "dmap-ai": {
      "type": "streamable-http",
      "url": "https://droughtanalysis.com/mcp"
    }
  }
}

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Tools

All tools are read-only (readOnlyHint: true, destructiveHint: false). They fetch and compute drought diagnostics from real climate data. No user data is written or stored.

debug_ping

Confirms the server is live and returns the current tool version and available free tools.

Input:  none
Output: server status, tool version, available tools list

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run_spi_table

Returns a Standardized Precipitation Index (SPI) table for a given location and time period.

Input:
  latitude        float    e.g. 42.03
  longitude       float    e.g. -93.62
  start_date      string   YYYY-MM-DD  (default: 1981-01-01)
  end_date        string   YYYY-MM-DD  (default: 2024-12-31)
  baseline_start  int      (default: 1981)
  baseline_end    int      (default: 2024)
  spi_scale       int      1–48 months  (default: 12)
  data_source     string   "nasa_power" | "era5"  (default: nasa_power)
  step            string   "yearly" | "monthly"   (default: yearly)
  yearly_method   string   "jan_dec_totals"       (default)
  category_scheme string   "classic_spi" | "usdm_style" | "percentile_band" | "kmeans"
  max_rows        int      (default: 1000)

Output: SPI table with date, precipitation, SPI value, and drought category per row

Example prompt:

"Show me the SPI-12 table for Ames, Iowa from 1981 to 2024."

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run_drought_severity_events

Detects and returns drought events (start, end, duration, minimum SPI, magnitude) using a configurable severity threshold.

Input:
  latitude / longitude / start_date / end_date / baseline_start / baseline_end
  spi_scale       int      (default: 12)
  data_source     string   "nasa_power" | "era5"
  step / yearly_method / category_scheme
  severity_threshold  string  SPI threshold, e.g. "-0.99", "-1.5"  (default: -0.99)

Output: drought events table (start date, end date, duration, min SPI, magnitude)

Example prompt:

"Find all drought events in Ames, Iowa from 1981 to 2024 using SPI-12 and a threshold of -1.0."

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run_wavelet_scalogram

Runs a continuous wavelet transform and returns a compact time–period power matrix (scalogram), highlighting high-power drought zones.

Input:
  latitude / longitude / start_date / end_date / baseline_start / baseline_end
  spi_scale       int      (default: 12)
  data_source     string   "nasa_power" | "era5"
  step / yearly_method
  max_periods     int      downsampled period axis limit  (default: 24)
  max_times       int      downsampled time axis limit    (default: 60)

Output: compact scalogram matrix, top high-power cells, period and time axes

Example prompt:

"Run a wavelet scalogram for SPI-12 in Ames, Iowa from 1981 to 2024 and show the high-power zones."

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run_drought_periodicity_analysis

Computes the global wavelet spectrum and identifies dominant and secondary drought periods (cycles) for a location.

Input:
  latitude / longitude / start_date / end_date / baseline_start / baseline_end
  spi_scale       int      (default: 12)
  data_source     string   "nasa_power" | "era5"
  step / yearly_method

Output: dominant period, top ranked periods by global power, global wavelet spectrum

Example prompt:

"Use DMAP-AI to run global wavelet analysis for SPI-12 in Ames, Iowa from 1981 to 2024. Then explain the dominant period."

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Data Sources

Source	Description	Coverage
nasa_power	NASA POWER (default)	Global, ~0.5° grid
era5	ERA5 / Copernicus reanalysis	Global, ~0.25° grid

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Supported Category Schemes

Scheme	Description
classic_spi	WMO standard SPI thresholds (default)
usdm_style	US Drought Monitor–style D0–D4 categories
percentile_band	Empirical percentile-based bands
kmeans	AI/ML k-means cluster labels

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Notes

• Free tools: SPI table, drought severity events, wavelet scalogram, periodicity/global wavelet spectrum
• Not included in the free MCP version: Copula analysis and other advanced licensed features
• All tools are stateless and idempotent — the same inputs always return the same outputs
• Data source is NASA POWER by default (no API key required)

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Links

• Live server: https://droughtanalysis.com/mcp
• Research version: https://droughtanalysis.com/DMAP_AI_App
• Privacy policy: https://droughtanalysis.com/privacy
• Terms of service: https://droughtanalysis.com/terms
• Contact / support: https://agrimetsoft.com/contact
• Developer: AgriMetSoft LLC

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Citation

If you use DMAP-AI outputs in research or publications, please cite DMAP-AI and the relevant data source (NASA POWER or ERA5/Copernicus).

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© AgriMetSoft LLC. DMAP-AI is a drought monitoring and analysis platform.