Load CARTO - Maps Api data to DuckDB
Build a CARTO - Maps Api to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the CARTO - Maps Api API base URL, auth, endpoints, and incremental loading.
The CARTO Maps API allows users to generate maps based on data hosted in their CARTO account. Everything needed to build a working CARTO - Maps Api → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.
Build your CARTO - Maps Api to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from CARTO - Maps Api to DuckDB and run it on dltHub
That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the CARTO - Maps Api API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →
Prefer to write it yourself? Every fact the agent uses is below.
CARTO - Maps Api API at a glance
| Base URL | https://gcp-us-east1.api.carto.com |
| Example endpoint | GET v1/connections |
| Authentication | All requests must be authenticated using an API Access Token or OAuth Access Token provided in the Authorization header — sent in the Authorization header, prefixed Bearer |
| Pagination | Not paginated |
| API reference | https://api-docs.carto.com/ |
These values come from the CARTO - Maps Api API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the CARTO - Maps Api API?
Authentication requires an Authorization header with a Bearer token. Format: Authorization: Bearer <API_ACCESS_TOKEN>
1. Get your credentials
To obtain API credentials in CARTO: 1. Log in to your CARTO Workspace. 2. Navigate to the 'Developers' section in the sidebar. 3. Select 'Credentials' to manage your access. 4. Click 'Create new' to generate an 'API Access Token'. 5. Provide a unique name for the token, select the required 'Allowed APIs' (such as Maps or SQL API), and specify the necessary connection grants. 6. Once saved, copy the generated API Access Token for use in your API headers. You can also find your regional 'API Base URL' in the same Developers section.
2. Add them to .dlt/secrets.toml
[sources.carto_maps_api_source] api_token = "your_api_access_token_here" api_base_url = "https://gcp-us-east1.api.carto.com"
dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.
What CARTO - Maps Api data can I load into DuckDB?
These are the CARTO - Maps Api endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| connections | /v1/connections | GET | List available connections | |
| tokens | /v1/tokens | GET | List tokens | |
| jobs | /v1/jobs | GET | List background jobs | |
| users | /v1/users | GET | List users | |
| workspace_resources | /v1/resources | GET | List workspace resources |
How do I load only new CARTO - Maps Api records?
The CARTO - Maps Api API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.
{"name": "connections", "endpoint": { "path": "v1/connections", # Replace with a field that increases on every write. "incremental": {"cursor_path": "REPLACE_ME", "initial_value": "2024-01-01T00:00:00Z"}, }}
On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.
What does the generated CARTO - Maps Api pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading sql and lds (or maps) from the CARTO - Maps Api API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def carto_maps_api_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://gcp-us-east1.api.carto.com", "auth": {"type": "bearer", "token": api_key}, }, "resources": [ {"name": "connections", "endpoint": {"path": "v1/connections"}}, {"name": "tokens", "endpoint": {"path": "v1/tokens"}} ], } yield from rest_api_resources(config) def load_carto_maps_api_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="carto_maps_api_pipeline", destination="duckdb", dataset_name="carto_maps_api_data", ) load_info = pipeline.run(carto_maps_api_source()) print(load_info) if __name__ == "__main__": load_carto_maps_api_to_duckdb()
Run it with python carto_maps_api_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.
How do I query CARTO - Maps Api data in DuckDB?
dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.
Python (pandas DataFrame):
import dlt data = dlt.pipeline("carto_maps_api_pipeline").dataset() df = data.connections.df() print(df.head())
SQL:
SELECT * FROM carto_maps_api_data.connections LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the CARTO - Maps Api to DuckDB pipeline in production?
The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.
- Deploy & schedule — run the pipeline as a managed job with automatic retries.
- Monitor — observable job queues, alerting, and load metrics for every run.
- Transform — promote raw CARTO - Maps Api loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load CARTO - Maps Api data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example value |
|---|---|
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.
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