Skip to main content
Glama

Open Meteo

by io.github.pipeworx-io
OverviewDiscussionsAdmin

Flood

flood
Read-onlyIdempotent

"Flood risk for [river]" / "river discharge forecast" / "will [river] flood" / "water levels at [location]" — daily river discharge forecast from the GloFAS global flood model. Returns predicted m³/s discharge up to 30 days ahead for any river-bearing lat/lng worldwide. Use for flood risk assessment, agriculture planning, hydrology research.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dailyNoDefault river_discharge
latitudeYes
longitudeYes
forecast_daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dailyNoDaily river discharge forecast data
latitudeNoQuery latitude
timezoneNoIANA timezone string
elevationNoElevation of the location in meters
longitudeNoQuery longitude
daily_unitsNoUnits for daily flood variables
generationtime_msNoAPI response generation time in milliseconds
utc_offset_secondsNoUTC offset in seconds

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "latitude": 47.5162,
+    "longitude": 14.5501
+  },
+  {
+    "forecast_days": 10,
+    "latitude": 41.9028,
+    "longitude": 12.4964
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "daily": {
+      "additionalProperties": {
+        "items": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "type": "array"
+      },
+      "description": "Daily river discharge forecast data",
+      "properties": {
+        "time": {
+          "description": "ISO 8601 date strings",
+          "items": {
+            "type": "string"
+          },
+          "type": "array"
+        }
+      },
+      "type": "object"
+    },
+    "daily_units": {
+      "additionalProperties": {
+        "type": "string"
+      },
+      "description": "Units for daily flood variables",
+      "type": "object"
+    },
+    "elevation": {
+      "description": "Elevation of the location in meters",
+      "type": "number"
+    },
+    "generationtime_ms": {
+      "description": "API response generation time in milliseconds",
+      "type": "number"
+    },
+    "latitude": {
+      "description": "Query latitude",
+      "type": "number"
+    },
+    "longitude": {
+      "description": "Query longitude",
+      "type": "number"
+    },
+    "timezone": {
+      "description": "IANA timezone string",
+      "type": "string"
+    },
+    "utc_offset_seconds": {
+      "description": "UTC offset in seconds",
+      "type": "integer"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A3.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds value by specifying that the output is daily discharge in m³/s for any river-bearing location, and that the forecast extends up to 30 days. It does not contradict annotations. Lacks details on data freshness or model version, but is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is moderately concise but starts with multiple example queries framed as questions, which adds redundancy. The core explanation (2 sentences) is effective, but the example list could be shortened. It front-loads the purpose well, but some content feels repetitive.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that an output schema exists (so return values are documented elsewhere), the description covers the main purpose and usage. However, it lacks explanation of behavior for non-river locations, parameter defaults, and error conditions. The low parameter schema coverage and absence of parameter details in the description reduce completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 25% (only the 'daily' parameter has a description, which is vague: 'Default river_discharge'). The tool description mentions latitude, longitude, and forecast_days implicitly but does not explicitly clarify their meaning, types, or constraints. With 4 parameters and a focused description, more parameter-level detail would aid correct usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a daily river discharge forecast, specifying the data source (GloFAS), unit (m³/s), and time horizon (30 days). It includes example queries that clarify the tool's scope, but does not explicitly distinguish it from the sibling tool 'forecast', which might also be weather-related.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states three use cases: flood risk assessment, agriculture planning, and hydrology research. This provides clear guidance on when to use the tool. However, it does not mention when not to use it or suggest alternative tools for different scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Open Meteo toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources