Reverse Geocoding Grounding Data

Overview

Lookup runs in two steps, both against bundled offline data. First the point given by `lat` and `lon` is placed in a country using country boundary polygons. Then the nearest entry in a US and Canada postal location dataset is found for that country, and its `city`, `state`, `state_abbr` and `zipcode` are returned. Coordinates in any other country are outside the dataset and are not supported.

Results are only as fine-grained as the dataset: the answer is the closest postal-code location, not the containing boundary, so points near a town or ZIP line can resolve to the neighbouring one. `latitudeClosest` and `longitudeClosest` are the matched location's coordinates, returned as strings, and `distance` is how far it lies from your point. `latitude` and `longitude` echo the input and `countryCode` is the two-letter code from the first step.

`nearestCities` is built by matching the resolved city name against a worldwide city list: it holds up to 20 unique city names that contain that name, such as Brooklyn Park and East Brooklyn for Brooklyn, in list order rather than by distance. `distance`, the closest coordinates, `estimatedCity` and `nearestCities` are null on the Free plan.

Live Test Reverse Geocoding Grounding Data Source →

The tool

Once your client is connected to the VerveContext server, this appears in its tool list as ReverseGeocodingGroundingData. It is read-only and open-world — it fetches and never mutates anything on your side — so most clients call it without asking you to confirm.

{
  "name": "ReverseGeocodingGroundingData",
  "arguments": {
    "lat": "40.714224",
    "lon": "-73.961452"
  }
}

You do not name the tool yourself; the model picks it. Asking about 40.714224 in the terms this source covers is enough for it to reach for ReverseGeocodingGroundingData on its own — naming it explicitly also works, and is the way to force the call.

Connecting

One server URL covers every source in the catalog, including this one. Authorization is OAuth: the client opens a browser once, and there is no key to paste into a config file.

{
  "mcpServers": {
    "vervecontext": {
      "url": "https://api.vervecontext.com/v1/mcp"
    }
  }
}

https://api.vervecontext.com/v1/mcp

Per-client setup — Claude, Cursor, VS Code, ChatGPT — is on the MCP setup page.

Arguments

These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made. Premium arguments are accepted on every plan but only take effect on plans that include them.

What the model gets back

The result carries a structuredContent object matching the tool's declared outputSchema, so a client reads fields without parsing prose. status is "ok" and error is null on success; a null field means the value was not available for that input, not that the call failed.

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{
  "status": "ok",
  "error": null,
  "data": {
    "zipcode": "11211",
    "state_abbr": "NY",
    "city": "Brooklyn",
    "state": "New York",
    "distance": 0.6501757300758664,
    "latitudeClosest": "40.712090",
    "longitudeClosest": "-73.95427",
    "countryCode": "US",
    "latitude": 40.714224,
    "longitude": -73.961452,
    "estimatedCity": true,
    "nearestCities": [
      "Brooklyn",
      "Brooklyn Park",
      "East Brooklyn",
      "Brooklyn Center",
      "Brooklyn Heights"
    ],
    "timezone": "America/New_York",
    "county": "Kings County",
    "countyFips": "36047",
    "geocodes": {
      "geohash": "dr5rsgyct",
      "plusCode": "87G8P27Q+MC",
      "dms": {
        "latitude": "40°42'51.2\"N",
        "longitude": "73°57'41.2\"W"
      }
    }
  }
}

Response fields

Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.

Why ground on it

A model can produce something that looks like this answer from its training data, and be confidently out of date or simply wrong. This source returns the current value in a shape you can check, which is the difference between an answer you can cite and one you have to hedge.

Point an evaluation at zipcode: it is the field most worth pinning a claim to, and it is either present and current or absent — never plausibly invented.

Failure modes

Errors come back as tool errors carrying a sentence the model can act on, not a bare status code. Error handling covers the full list.

A call costs 6 credits each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.

Use cases

Fleet Telematics Tracking

Logistics systems match vehicle GPS pings against city and state boundaries to generate human-readable trip summaries for dispatchers.

Mobile Photo Geotagging

Camera apps read coordinate metadata from uploaded photos to display the city and state where each picture was taken.

Delivery Address Autofill

When a customer shares device coordinates at checkout, ecommerce apps automatically populate the city, state, and ZIP code fields.

Field Service Dispatch

To assign incoming repair tickets, maintenance platforms convert technician coordinates into local municipality names and postal codes.

Other ways to use Reverse Geocoding Grounding Data

Set up Reverse Geocoding Grounding Data on VerveContext, or reach the same source a different way. Your VerveContext account and credits work on all of them — one key, one balance.

Related

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