LatLong Maps

Turn CSV or Excel data into styled choropleth and categorical maps of India from plain language.

CommunityOnlineAPI key requiredGlobalFreeRead-only

What it can do

    What data it sees

    Do you need an account

    An API key from the service settings is required

    Turn CSV or Excel data into styled choropleth and categorical maps of India from plain language.

    How to connect

    How to connect LatLong Maps to Claude

    The server address to paste into Claude settings:

    https://geocp.latlong.ai/mcp/

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect LatLong Maps to ChatGPT

    The server address to paste into ChatGPT settings:

    https://geocp.latlong.ai/mcp/

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect LatLong Maps to Cursor

    The server address to paste into Cursor settings:

    https://geocp.latlong.ai/mcp/

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (4)

    Raw names from tools/list. Only developers need these.

    create_uploadStart a client-direct file upload for large CSV/XLSX files. Returns a presigned put_url and an opaque upload_id. Steps: 1) call create_upload with file_name, 2) HTTP PUT the raw file bytes to put_url using the returned headers, 3) pass upload_id to question_to_map, parse_file, or render_map. Preferred over file_base64 for anything beyond a few KB — the bytes go straight to storage instead of riding inside the tool call.
    get_capabilitiesReturn the server's capability matrix (supported map types, geo types, output formats, and classification methods).
    process_uploadValidate and ingest a file uploaded via create_upload. Runs size, virus, and content-safety checks, parses CSV/XLSX/JSON, and returns an upload_id plus advisory intent (no raw rows). IMPORTANT: to make a map, call question_to_map and pass this upload_id — and pass the SAME upload_id on every follow-up question about this file (e.g. 'now show it by district'). The response includes a ready-to-use next_actions entry with upload_id already filled in; prefer firing that. Rejects infected or injected files (nothing is kept in that case).
    question_to_mapRender a geographic map from a question. TO MAP A FILE (CSV/XLSX/JSON) — you MUST upload it first, in this order: 1) call create_upload {file_name} -> returns { upload_id, put_url } 2) HTTP PUT the raw file bytes to put_url (use the returned headers) 3) call process_upload {upload_id, ...your intent} -> validates the file 4) call question_to_map {question, upload_id, geo_column?, value_column?} Do NOT call question_to_map with a file path or the raw bytes for an uploaded document — pass the upload_id from step 1. Reuse the SAME upload_id on every follow-up about that file (e.g. 'now show it by district'). Ways to provide data: 1. Uploaded document (preferred): {"question": "show total by pincode", "upload_id": "<from create_upload>", "geo_column": "pincode", "value_column": "total"} 2. Question only (DB): {"question": "ola sales in delhi ncr"} 3. CSV inline (small only): {"question": "show sales", "csv": "state,sales\nMaharashtra,500", "geo_column": "state", "value_column": "sales"} INTENT (all optional; if you know them, pass them — your values win over auto-detection): geo_column, value_column, geo_level (state|district|pincode|rto|city|ac|pc), map_type, state_hint. If you omit upload_id, the server falls back to your most recent upload; passing it is more reliable. If value_column is 'total' and absent from the data, all numeric columns are summed automatically. Supported geo types: state, district, pincode, rto, city, ac, pc.