cartodb/agent-skills

carto-import-export-data

Import geospatial files into the data warehouse via CARTO, export results back out, and prepare tilesets for fast map rendering.

查看源码

使用方法

  1. 复制安装命令,在自己的智能体环境安装前先检查源码包。
  2. 从原始文档核对所需工具、凭据和支持的宿主。
  3. 说明输入材料与期望交付物,并对照来源检查输出。
npx skills add https://github.com/cartodb/agent-skills --skill carto-import-export-data

开始前需了解

  • 安装不包含模型订阅、API 额度或访问文件的权限。
  • 仓库星数和安装量反映活跃情况,不等于独立质量或安全测试。
仓库原始内容

按源仓库内容呈现,保留标题、案例、代码、表格、链接以及原文引用的演示图片。

carto-import-export-data

Move data into the warehouse from local files / URLs, pull data out, transfer tables between connections, and prepare tilesets for performant rendering of large geospatial datasets.

Access-path routing. With the CARTO MCP server attached (OAuth session), route interactive moves through import_data, export_data, and transfer_data (each method: submit|status), and materialize tilesets with execute_async_query. Fall back to the carto import / carto sql job CLI for scripted/bulk loads, headless pipelines, or when the server isn't attached — and note that over a token-authenticated MCP session the import/export/transfer tools are hidden (read/discovery subset only), so authoring moves there go via the CLI too. carto activity export (usage data → local disk) is CLI-only, no MCP equivalent. Format, size-limit, and destination-syntax guidance below applies on every path. Detection signals: `carto-basics/references/access-paths.md`.

When to use this skill

  • The user has a CSV / GeoJSON / Shapefile / GeoParquet file and wants it queryable in the warehouse.
  • The user wants to refresh an existing table from a remote URL, or copy a table between connections.
  • The user wants to render a 10M+-row spatial dataset on a map (needs tileset preparation).
  • The user is bulk-exporting CARTO activity data to disk for offline analysis.

To query a file already in the warehouse, jump to `carto-query-datawarehouse`. To discover what's already there, `carto-explore-datawarehouse`.

Quick reference

MCP (OAuth session) — submit then poll:

import_data   { method: "submit", source: {url|file}, connection, destination, overwrite? }
export_data   { method: "submit", ... }   → status with the returned job id
transfer_data { method: "submit", source_connection, destination_connection, ... }

CLI fallback (scripted / headless / no server / token session):

bash
# Import a local file (or --url for a remote source; --async to poll separately; --overwrite to replace)
carto import --file ./data.csv --connection carto_dw --destination project.dataset.table

What's in this skill

TopicReference
Importing — import_data / carto import flags, formats, size limits, asyncreferences/imports.md
Tileset preparation for large mapsreferences/tilesets.md
Exporting & transferring: warehouse-native unloads, export_data/transfer_data, activity exportreferences/exports.md

Always-on guidance

  • `--connection` / `connection` is the connection name*** (discover it with explore_data method: list_connections, or carto connections list --json), not the warehouse project ID.
  • `destination` is the fully-qualified target name in the warehouse's syntax: project.dataset.table (BigQuery), DATABASE.SCHEMA.TABLE (Snowflake), schema.table (Postgres/Redshift), catalog.schema.table (Databricks), SCHEMA.TABLE (Oracle).
  • 1 GB hard limit per file (CARTO-side, not a warehouse limit). For larger files, pre-stage to cloud storage and import from a presigned URL.
  • Disable autoguessing (--no-autoguessing on the CLI) when you've prepared a precise schema and don't want CARTO to second-guess types — especially numeric-looking columns that should stay string, like ZIP codes.
  • Imports/exports are async at the API level. MCP import_data/export_data return a job id — poll with method: "status". The CLI polls to completion by default; pass --async to return immediately with a job id.
  • Tilesets follow import → materialize tileset table (`execute_async_query` or `carto sql job`) → reference the tileset in a map. The tileset is created in the warehouse, not by the mover itself.

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