Land Parcels within a Radius API, Tamil Nadu

Example

Request

curl -X POST https://verified.realestate/api/v1/tools/radius_discovery \
  -H "Authorization: Bearer $LANDLENS_KEY" \
  -H "Content-Type: application/json" \
  -d '{"lat":12.901,"lng":80.2279,"radius_m":300}'

Responsereal answer

{
  "ok": true,
  "status": "ok",
  "data": {
    "found": true,
    "centre": { "lat": 12.901, "lng": 80.2279 },
    "radius_m": 300,
    "page": 1,
    "page_size": 30,
    "total": 275,
    "capped": false,
    "area_unit": "acres",
    "sorted": "nearest first",
    "parcels": [
      {
        "survey": "722",
        "survey_number": "722",
        "district_code": "2",
        "taluk_code": "11",
        "village_code": "013",
        "distance_m": 0,
        "area_acres": 4.78,
        "area_hectares": 1.934,
        "is_govt": false,
        "boundary_geojson": "{\"type\":\"MultiPolygon\",\"coordinates\":[[[[80.2277681,12.901071], ...]]]}",
        "rural_urban": "rural"
      },
      {
        "survey": "481/13",
        "survey_number": "481",
        "sub_division": "13",
        "district_code": "2",
        "taluk_code": "11",
        "village_code": "013",
        "owner_name": "M/S.CHENNAI METRO RAIL LIMITED",
        "owner_source": "revenue record (as per record)",
        "is_govt": false,
        "rural_urban": "rural",
        "...": "..."
      }
    ]
  },
  "credits_quoted": 4,
  "credits_charged": 4,
  "credits_waived": 0
}

A real answer at Sholinganallur, Chennai, trimmed: two of 30 parcels on the page, boundaries cut short, and empty fields left out. Parcels held by private persons are left out of this sample.

What it returns

One call, one page of up to 30 parcels, nearest first. found is false (status not_found) when nothing matches, and message says why.

Field	What it holds
`parcels[]`	Each parcel: survey (with sub-division), survey_number, sub_division, district_code, taluk_code, village_code, distance_m, area_acres, area_hectares, is_govt, boundary_geojson and rural_urban.
`owner_name, owner_name_ta, owner_source`	Where the revenue register holds the parcel: the recorded owner in English and Tamil ("+N more" when there are several) and which register it came from.
`total, page, page_size, capped`	How many parcels lie in the radius, which page this is, and whether the sweep stopped at its cap.
`centre, radius_m, sorted`	The point and radius searched, and the order (nearest first).
`message`	When nothing matched: whether the filters ruled every parcel out, the point is outside Tamil Nadu, or the area is not mapped.

Inputs

The JSON body of the POST is the arguments. Nothing is required by the schema, but over the API lat, lng and radius_m all are: without them the call answers not_found and charges nothing.

Argument	Type	What to send
`lat`	number	Latitude of the centre, e.g. 12.9010.
`lng`	number	Longitude of the centre, e.g. 80.2279.
`radius_m`	integer	Radius in metres, e.g. 5000 for 5 km.
`min_area_acres`	number	Smallest parcel to list, in acres.
`max_area_acres`	number	Largest parcel to list, in acres.
`exclude`	array	Leave out parcels touching any of: industrial, eco_sensitive, flood, reserve_forest, aquifer, road_widening, govt.
`page`	integer	Page number, 30 parcels a page. Default 1.

Code

Set LANDLENS_KEY to your key. In an AI app, connect https://verified.realestate/mcp once and ask in plain words instead. In Postman, download this API's collection, import it (File, Import) and set apiKey.

curl -X POST https://verified.realestate/api/v1/tools/radius_discovery \
  -H "Authorization: Bearer $LANDLENS_KEY" \
  -H "Content-Type: application/json" \
  -d '{"lat":12.901,"lng":80.2279,"radius_m":300}'

import os, requests

r = requests.post(
    "https://verified.realestate/api/v1/tools/radius_discovery",
    headers={"Authorization": f"Bearer {os.environ['LANDLENS_KEY']}"},
    json={
        "lat": 12.901,
        "lng": 80.2279,
        "radius_m": 300
    },
    timeout=30,
)
body = r.json()
print(body["status"], body["credits_charged"], body["data"])

const res = await fetch("https://verified.realestate/api/v1/tools/radius_discovery", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.LANDLENS_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "lat": 12.901,
    "lng": 80.2279,
    "radius_m": 300
  }),
});
const body = await res.json();
console.log(body.status, body.credits_charged, body.data);

Find every parcel of 3 acres or more within 5 km of Sriperumbudur bus stand, leaving out flood-prone land and government land.

Your AI finds the point, runs the sweep with those filters, and says which of your conditions it could not filter by.

Responses

Every answer has the same envelope. What status can say for this call:

status	What it means
`ok`	At least one parcel matched. Charged for a sweep (see pricing).
`not_found`	No parcel matched, no centre or radius was sent, or the register did not answer. message or error says which. Not charged.
`insufficient_credits`	HTTP 402, with the credits needed, your balance and where to top up.
`error`	The call failed on our side. Nothing is charged.

Where the data comes from

Register

The state cadastral boundary layer (the FMB survey parcels), with owners from the revenue A-register and the town survey register, and government land from the register's own classification.

Coverage

Survey parcels mapped in the state cadastral layer across Tamil Nadu. The layer does not cover every village evenly; a point outside Tamil Nadu, or in a thinly mapped area, returns few or none and the answer says which.

How current

Read from our copy of the state cadastral layer, downloaded again about once a year, and our copy of the revenue registers for owners.

How we read it

Every parcel that falls within the radius is listed with its distance from the point (0 for the parcel the point sits in), filtered by size and the exclusion layers you name. When a sweep is empty, it is re-run without filters to tell you whether the filters or the mapping explain it.

Who uses it

Warehousing and industrial developers

List every 5 acre parcel within 10 km of a highway junction or a port, outside flood and eco-sensitive zones.

Land aggregators

Map the parcels around a parcel already held, nearest first, to plan the next approach.

Banks and valuers

See the neighbouring survey numbers and their sizes around a mortgaged property.

Limits and good practice

No land use, wet or dry, vacancy or guideline value filter. Check classification per parcel afterwards with igr_classification or zone_check.
The cadastral layer is uneven across the state. Few results can mean a thinly mapped area, not an empty one.
An owner shown is the name in the revenue register, not a title opinion.
A large radius in a dense area holds thousands of parcels. Use a size filter, or page through 30 at a time.
Tamil Nadu only.

Pricing

4 credits per sweep

A sweep costs 4 credits, charged on the first page that returns parcels. The next pages of the same sweep are free up to the fifth; each further block of five pages carries a smaller charge, shown in credits_charged. A sweep that finds nothing is not charged. Credits come from the same LandLens wallet as the chat and the minis. How billing works.

Calling at volume?

For thousands of calls a month, a portfolio sweep or a platform built on these registers, we quote a customised bulk price, with invoicing to match.

WhatsApp 99961 29996

Questions

Is there an API to find land parcels near a location?

Yes. LandLens lists every mapped survey parcel within a radius of a point in Tamil Nadu, nearest first, with distance, size, boundary and recorded owner, over plain HTTPS or as an MCP tool.

How much does a radius sweep cost?

A sweep costs 4 credits, which covers its first five pages. A sweep that finds nothing is not charged.

How large a radius can I use?

Any, but results come 30 to a page. For a radius of several kilometres, add a minimum size so the list holds the parcels you would actually approach.

Can I exclude government or flood-prone land?

Yes. exclude takes govt, flood, industrial, eco_sensitive, reserve_forest, aquifer and road_widening. Those seven are the only exclusions.