Locality Value API: compare Tamil Nadu street guideline rates

Example

Request

curl -X POST https://verified.realestate/api/v1/tools/locality_value_context \
  -H "Authorization: Bearer $LANDLENS_KEY" \
  -H "Content-Type: application/json" \
  -d '{"street_name":"Adhinarayana Puram 1st street","village":"Velachery","sro":"Velacheri","zone":"Chennai"}'

Responsereal answer

{
  "ok": true,
  "status": "ok",
  "data": {
    "found": true,
    "source": "Street guideline value register (2024 rates)",
    "unit": "Rs. per sq.ft for the street as registered",
    "bands": {
      "village": { "name": "Velachery", "priced_streets": 2691, "min": 3300, "median": 4400, "max": 13200, "cheapest_street": "Ambedkar colony : -", "dearest_street": "Alacritiy Apartments (100 feet Byepass Road)" },
      "sro": { "name": "Velacheri", "priced_streets": 4514, "min": 1650, "median": 3850, "max": 13200, "cheapest_street": "Anran Kuttai", "dearest_street": "Alacritiy Apartments (100 feet Byepass Road)" },
      "zone": { "name": "Chennai", "priced_streets": 53405, "min": 100, "median": 2700, "max": 27500, "cheapest_street": "AADHAVAN GARDEN", "dearest_street": "G.N.CHETTY ROAD(PART 1 ANNA FLY OVER TO DR. NAIR ROAD)" }
    },
    "sro_office": {
      "name": "Velacheri",
      "district": "Chennai South",
      "address": "NO.17/39, RAJALAKSHMI NAGAR 3RD MAIN ROAD, VELACHERY, CHENNAI 600042",
      "phone": "044-22553736",
      "email": "[email protected]"
    },
    "street": {
      "name": "Adhinarayana Puram 1st street",
      "village": "Velachery",
      "sro": "Velacheri",
      "zone": "Chennai",
      "classification": "Residential Class II Type - III",
      "guideline_2024": 3850,
      "earlier_years": { "2023": 3500, "2017": 2345, "2012": 3500, "2007": 1500 },
      "position": { "percentile_in_village": 6, "vs_village_median": -13, "summary": "Near the bottom of the village range." }
    }
  },
  "credits_charged": 1
}

A real answer from the API, as returned.

What it returns

One call, one answer. found is false (status not_found, nothing charged) when no priced street is held for the place named.

Field	What it holds
`bands.village, bands.sro, bands.zone`	For each ring: name, priced_streets, min, median and max rate, cheapest_street and dearest_street.
`street`	The matched street: name, village, sro, zone, classification, guideline_2024 and earlier_years (2023 back to 2002, where the register records them).
`street.position`	percentile_in_village (how far along the village's lowest to highest rate the street sits, 0 to 100), vs_village_median (per cent above or below the median) and summary in plain words.
`sro_office`	The sub registrar office: name, district, address, phone and email.
`unit, source`	Rupees per square foot as registered, from the 2024 street register.
`street_not_found, village_not_found, message`	Set when a street or village you named is not in the register, so the area picture is never mistaken for that street's.

Inputs

The JSON body of the POST is the arguments. Send at least one of street_name, village, sro or zone. guideline_value returns the village and office to send.

Argument	Type	What to send
`street_name`	string	The street to benchmark. Part of the name is enough. Leave it out for the village picture alone.
`village`	string	The village or town as the guideline register names it, e.g. Velachery.
`sro`	string	Sub-registrar office name
`zone`	string	Registration zone, e.g. Chennai

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/locality_value_context \
  -H "Authorization: Bearer $LANDLENS_KEY" \
  -H "Content-Type: application/json" \
  -d '{"street_name":"Adhinarayana Puram 1st street","village":"Velachery","sro":"Velacheri","zone":"Chennai"}'

import os, requests

r = requests.post(
    "https://verified.realestate/api/v1/tools/locality_value_context",
    headers={"Authorization": f"Bearer {os.environ['LANDLENS_KEY']}"},
    json={
        "street_name": "Adhinarayana Puram 1st street",
        "village": "Velachery",
        "sro": "Velacheri",
        "zone": "Chennai"
    },
    timeout=20,
)
body = r.json()
print(body["status"], body["credits_charged"], body["data"])

const res = await fetch("https://verified.realestate/api/v1/tools/locality_value_context", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.LANDLENS_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "street_name": "Adhinarayana Puram 1st street",
    "village": "Velachery",
    "sro": "Velacheri",
    "zone": "Chennai"
  }),
});
const body = await res.json();
console.log(body.status, body.credits_charged, body.data);

Is the guideline value on Adhinarayana Puram 1st Street, Velachery high or low for the area? Which streets in Velachery are the dearest?

Your AI benchmarks the street against its village, office and zone and names the extremes.

Responses

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

status	What it means
`ok`	At least one band was found. Charged.
`not_found`	No priced street for the place named, or nothing was named. Nothing is charged.
`insufficient_credits`	HTTP 402: the balance does not cover the call, with the credits needed and your balance.

Where the data comes from

Register

The street guideline register of the Tamil Nadu Registration Department (the rates for towns and cities, set street by street), with the 2024 rate and earlier revisions, and the department's directory of sub registrar offices.

Coverage

454,112 street and locality entries across Tamil Nadu. For scale: the Chennai zone alone holds 53,405 streets priced in 2024.

How current

The 2024 rates of the street register. A band is computed once a day at most; the register changes only when the department revises it.

How we read it

The street is matched exactly first, then by the start of its name, then anywhere in the name, then with dots, spaces and punctuation ignored (so G.N. Chetty Road finds G.N.CHETTY ROAD). Place names are matched the way the register spells them (T.Nagar is Tnagar). Each band counts only streets with a 2024 rate.

Who uses it

Valuers

Put the subject street's guideline rate against the village range before writing a valuation.

Buyers and brokers

Answer "is this street dear for the area" with the register's own figures.

Analysts and developers

Find the cheapest and dearest streets in an office or zone when scouting.

Limits and good practice

Street register only: towns and cities rated street by street. Village land rated by survey number is the guideline_value call.
A partial street name takes the highest-rated match. Send the full name, or the village and office, when a name is common.
The bands compare 2024 guideline rates, not market prices.
percentile_in_village is a position on the range from the lowest to the highest rate, not a rank among streets.

Pricing

1 credit per answer

Each call costs 1 credit, and nothing when no priced street is found. 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