Weather & Geo Intel MCP

Geocode

geocode

Read-onlyIdempotent

Convert a US street address OR a city/town name into latitude/longitude coordinates, using US Census data. Accepts both '1600 Pennsylvania Ave NW, Washington DC' and 'Chicago, IL' - a place name returns the centroid of the city. Call this first whenever you have a location as text and need coordinates for the weather or elevation tools. US locations only.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`address`	Yes	A US street address ('1600 Pennsylvania Ave NW, Washington DC') or a city or town ('Chicago, IL', 'Springdale, Arkansas')

Output Schema

TableJSON Schema

Name	Required	Description
`query`	No
`source`	No
`matches`	No
`matched_by`	No
`provenance`	No	Where this answer came from. served_at is when Datakoot answered (UTC); upstream lists the official sources consulted. Datakoot may serve a briefly cached copy, so the source's own observation can be older than served_at.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 8, 2026

addedOutput schema / properties / provenance

Added value: +{
+  "description": "Where this answer came from. served_at is when Datakoot answered (UTC); upstream lists the official sources consulted. Datakoot may serve a briefly cached copy, so the source's own observation can be older than served_at.",
+  "properties": {
+    "may_be_cached": {
+      "type": "boolean"
+    },
+    "publisher": {
+      "type": "string"
+    },
+    "served_at": {
+      "format": "date-time",
+      "type": "string"
+    },
+    "upstream": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}

Changed1 schema field changedOct 3, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "matched_by": {},
+    "matches": {},
+    "query": {},
+    "source": {}
+  },
+  "type": "object"
+}

First observedSep 6, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive behavior, so the safety profile is covered. The description adds real context beyond that: the US Census data source, the geographic restriction to US locations, and the important behavioral detail that a place name returns the city centroid rather than a point address.

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

Conciseness5/5

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

Three sentences, zero filler, with the core capability and accepted input formats front-loaded before the workflow guidance and the US-only constraint. Every sentence carries distinct information.

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

Completeness5/5

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

An output schema exists, so return values need not be described. The description covers accepted input forms, data source, geographic scope, place-name return semantics, and where the tool fits in the weather/elevation workflow – everything needed to invoke it correctly.

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

Parameters4/5

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

Schema coverage is 100% and there is a single parameter, so the baseline is 3. The description goes beyond the schema by clarifying the semantic difference between the two accepted input shapes, notably that a city/town name yields a centroid rather than a rooftop-level point.

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

Purpose5/5

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

States a specific verb (convert) and resource (US street address or city/town name into lat/long coordinates), and names the data source (US Census). It clearly distinguishes itself from siblings weather_forecast, weather_current, weather_alerts, earthquakes and elevation by being the coordinate-lookup step.

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

Usage Guidelines5/5

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

Explicitly says when to call it ('Call this first whenever you have a location as text and need coordinates') and names the downstream tools that consume its output (weather or elevation). It also states a hard exclusion: 'US locations only.'

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

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