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BumiAtlas MCP

Lakshadweep: Kavaratti land parcels

Survey parcels on Kavaratti, Lakshadweep, from the Bharatmaps cadastral layer as tools an AI assistant can call: find the parcel at a point or by survey number, see its area, and see it on a map with its neighbours.

Server URL

Streamable HTTP with OAuth. The first time you connect, your client opens a browser window to sign in with Google; no API key needed.

https://bumiatlas.com/mcp/lakshadweep

Connect

Claude (claude.ai, desktop)
Settings → Connectors → Add custom connector, paste the URL, then Connect and sign in with Google.
Claude Code
claude mcp add --transport http bumiatlas-lakshadweep https://bumiatlas.com/mcp/lakshadweep
ChatGPT
Settings → Apps & Connectors → Advanced → Developer mode, then Create with the URL and OAuth authentication.
Cursor
in ~/.cursor/mcp.json
{
  "mcpServers": {
    "bumiatlas-lakshadweep": {
      "url": "https://bumiatlas.com/mcp/lakshadweep"
    }
  }
}

Tools

Tool names and descriptions are in English, which models understand best; your assistant still answers in your language.

IN_parcel_search
Find Indian cadastral parcels by location, ULPIN, or number in a village, with each parcel's whole record. query takes coordinates as 'latitude, longitude' (e.g. 15.3433, 74.1764), a Madhya Pradesh ULPIN, a parcel id from an earlier result ('ga-123'), or a khasra/survey number ('35/1') with state and village: a village name in Rajasthan, Goa and Delhi ('Calem', 'Mundka'), the village's LGD code in Madhya Pradesh. state and village without a number list the village's parcels, paged with offset. Assam is searchable by coordinates only. With coordinates it returns parcels containing the point (distance 0), then the nearest within `radius` metres, closest first. Each parcel has id, state, number, village, record (the state's own fields), mapArea (m²) and bbox. Set include_geometry for each boundary as GeoJSON (keep limit small). Use IN_parcel_image to see a parcel and its neighbours.
querystring
'latitude, longitude', a ULPIN, a parcel id (ga-123), or a khasra/survey number with state and village
statestring
rj Rajasthan, mp Madhya Pradesh, ga Goa, as Assam, ld Lakshadweep, dl Delhi; needed with a number or village
villagestring
Village name (Rajasthan, Goa, Delhi) or LGD code (Madhya Pradesh)
radiusnumber
Search radius in metres around coordinates(default 25)
limitinteger
Maximum results(default 20)
offsetinteger
Skip this many matches of a number or name search, to page through them(default 0)
include_geometryboolean
Include each boundary as a GeoJSON MultiPolygon(default false)
IN_parcel_image
A map image centred on an Indian parcel (id, 'rj-123' from IN_parcel_search) or a point (query), with every parcel in view outlined and labelled with its khasra or survey number, so you can see which parcel is where. The parcel passed as id is drawn in red with a larger label; a query point is a red dot. Returns the parcels in view as JSON (label, id, number, village, area in m²; labelled: false where its label didn't fit), then one JPEG per basemap. Basemaps: satellite (Esri World Imagery, often a few years old), hybrid (the same imagery with road and place names), streets and topo (Esri's street and topographic maps). Pass several to compare, e.g. ['satellite', 'streets'] to match buildings with street names. Parcel outlines are yellow on imagery and magenta on maps. The portals' maps are digitised village sheets: offsets of 10 m or more from imagery are common. A scale bar is at bottom left. Labels are left off where they'd overlap; call again with a smaller radius to read them. Each image costs about as much context as 1,000 words, so ask for what you need.
idstring
Parcel id (rj-123, ga-45), drawn in red
querystring
'latitude, longitude' to centre on instead of a parcel
radiusnumber
Metres from the centre to the image edge. Default: fits the parcel with a margin, or 80 m around a point
basemapsarray
One image per basemap(default ["satellite"])
sizeinteger
Image width and height in pixels(default 768)

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