LatLong Maps

ai.latlong由 latlong.ai 發布官方發布者v1.0更新於 Oct 24, 2026

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

已驗證Streamable HTTP可網頁執行位置與生活資料與分析

概覽

AI 產生的概覽

遠端 MCP 伺服器,把上傳的 CSV 或 Excel 資料轉成印度地圖,並提供地理編碼、逆地理編碼與自然語言地圖問答。

可以做什麼
  • 上傳 CSV 或 XLSX 檔案供伺服器端擷取,取得可重複使用的 file_key
  • 把上傳檔案中的地址地理編碼為經緯度,可指定或自動辨識地址欄位
  • 把上傳檔案中的經緯度逆地理編碼為地址
  • 依自然語言問題與 file_key 產生分級著色或分類地圖
  • 回傳伺服器能力矩陣:地圖類型、地理類型、輸出格式與可用工具
適用情境
適合手上有含地址、郵遞區號或座標的表格資料、想不寫 GIS 程式就取得印度地圖的情況,也適合讓助理透過產生地圖來回答位置相關問題。
執行需求
遠端 streamable HTTP 端點,不需本機套件。需要 LatLong 存取權杖(JWT),透過 X-Authorization-Token 標頭傳送。上傳檔案在伺服器端依大小上限與掃描政策處理。
安裝前請注意
每次呼叫都必須提供 X-Authorization-Token 這項密鑰。上傳的 CSV/XLSX 資料會送往第三方服務進行擷取、掃描與製圖,請避免上傳敏感或個人資料。上傳與製圖會在伺服器端寫入資料。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 LatLong Maps,將其新增到工作區。
  2. 連接 X-Authorization-Token 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/ai.latlong%2Fmap-mcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "latlong-maps": {
      "type": "http",
      "url": "https://geocp.latlong.ai/mcp/",
      "headers": {
        "X-Authorization-Token": "<YOUR_API_KEY>"
      }
    }
  }
}

工具

5

geocode

Geocode addresses from an uploaded CSV or XLSX file into latitude/longitude. Pass a file_key from upload_file. Column selection: if you know it, pass address_column (or address_columns for several). Otherwise the server asks the geo-match service to detect it. When the answer is not unambiguous — several address columns, a weak match, or only structured columns like District/State/PIN that must be combined — the response is status=clarification_required with candidates and ready-to-fire guidance actions. Present the choice to the user and re-call with their answer; never invent a column name. The result overwrites the same file_key as a new version, plus a small preview, not the full rows. Pass that file_key to question_to_map to map the coordinates, or hand the user file_url (a signed download link, when present) to fetch the file directly.

輸入參數sheetjob_idfile_keyforce_newaddress_columnaddress_columnscompose_columns

get_capabilities

Return the server's capability matrix: supported map types, geo types, output formats, classification methods, and the list of tools available in this process (which varies by configuration). Call this first to discover what the server can do.

無需輸入參數。

question_to_map

Render a geographic map from your data. Call upload_file first to ingest a CSV/XLSX file, then pass the returned file_key: {"question": "show total by pincode", "file_key": "mcp-uploads/<user-id>/2026/01/15/<uuid>.csv"}. The file_key is reusable — for additional questions on the same file, pass the same file_key again without re-uploading. Alternatively, pass rows directly as 'data' (e.g. from the upload_file preview): {"question": "show total by pincode", "data": [<rows>]} geo_column and value_column are preferred if easily identifiable from the column names, but not required — the server auto-detects them using a geo-match service that matches your data against known Indian geographies (states, districts, ACs, PCs, pincodes, RTOs, cities). Hints: geo_column usually contains place names (state, district, city, pincode, constituency) or numeric codes (pincode=560049); value_column usually contains the metric to plot (sales, count, total, percentage) or a category (party affiliation, status, type). If value_column is 'total' and doesn't exist in data, all numeric columns are summed automatically. String value columns render as categorical maps (each distinct value gets its own color, e.g. party affiliation). If the server cannot determine which columns to use, it returns a 'clarification_required' response with suggested columns and guidance — pick a geo_column and value_column from the suggestions and re-call. Supported geo types: state, district, pincode, rto, city, ac, pc. Points mode: if your file has latitude/longitude columns (e.g. from a prior geocoding step, or coordinates you already had) and your question asks to plot/pin/mark locations ("plot my stores", "show me the outlet locations", "mark these points"), the server detects the coordinate columns automatically and renders markers instead of shaded regions — no geo_column/value_column needed. The boundary lines drawn beneath the markers and how far the map zooms are chosen automatically from where the

輸入參數datasheetstyletablefile_keymap_typequestion必填geo_levelgeo_columnstate_hintenrich_withdetected_geo另有 3 個

reverse_geocode

Turn latitude/longitude coordinates in an uploaded CSV or XLSX into addresses. Pass a file_key from upload_file. Column selection: pass latitude_column and longitude_column, or latlong_column for a single combined column, or coordinate_pairs for several sets. Otherwise the server detects them. When the answer is not unambiguous — several coordinate columns, a weak match, coordinates outside the supported region, or coarse whole-number values — the response is status=clarification_required. Present the choice to the user and re-call with their answer. Results are written back into the uploaded file: the response carries file_key, a signed file_url, and a small preview. Each pair adds address, pincode, landmark and status columns.

輸入參數sheetjob_idfile_keyforce_newlatlong_columnlatitude_columncoordinate_pairslongitude_columnaccept_low_precision

upload_file

Upload a CSV or XLSX file for server-side ingestion under policy (auth, size cap, malware scan, injected-intent scan) and receive a file_key. This is the first step before calling question_to_map with your own data. Step 1: Call upload_file with file_name, file_size, and question. The response contains a signed upload_url and a curl command — run the curl command to POST the file bytes. The curl response contains file_key, columns, a row preview, and optionally 'intent' (geo-match service detected geo_column, geo_level, value_column, map_type, confidence) and 'guidance' (a ready-to-fire question_to_map action with all detected parameters pre-filled). Forward the intent fields into question_to_map to skip auto-detection and render immediately. For multi-sheet XLSX: the curl response is 'sheet_selection_required' with a file_key and sheets list. Pass file_key and sheet to question_to_map (or any other tool that accepts file_key) — do not call upload_file again. After upload, pass the returned file_key to question_to_map to render a map from the full dataset. The file_key is reusable — for additional questions on the same file, pass the same file_key again without re-uploading. When the upload response includes 'guidance', use its next_actions directly for a zero-round-trip render.

輸入參數sheetfile_keyquestionfile_name必填file_size必填

版本歷史

1
  1. v1.0最新Sep 16, 2026

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