Load Vtex data to DuckDB
Build a Vtex to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Vtex API base URL, auth, endpoints, and incremental loading.
VTEX provides a suite of e-commerce APIs for managing store operations, logistics, orders, and user authentication across the VTEX platform. Everything needed to build a working Vtex → 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 Vtex to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Vtex 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 Vtex 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.
Vtex API at a glance
| Base URL | https://{accountName}.{environment}.com.br |
| Example endpoint | GET api/dataentities/{data_entity}/scroll |
| Authentication | API requests require either application key headers or a user token cookie header — sent in the request header |
| Pagination | Cursor-based via _token, page size via _size. For the Master Data Scroll API, the token is obtained via the 'X-VTEX-MD-TOKEN' response header in the first request and passed as the '_token' query parameter in subsequent requests. The page size is set using the '_size' parameter in the first request only. Pagination in the Master Data Search API uses the 'REST-Range' header for range-based pagination (e.g., resources={x}-{y}). |
| Incremental field | _token |
| Record id | id |
| API reference | https://developers.vtex.com/docs/guides/api-authentication-using-api-keys |
These values come from the Vtex API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Vtex API?
Authentication is typically performed using an appKey-appToken pair passed in the 'X-VTEX-API-AppKey' and 'X-VTEX-API-AppToken' headers, or by passing a user token in the 'VtexIdclientAutCookie' header.
1. Get your credentials
- In your VTEX Admin, click your profile avatar (top right corner). 2. Navigate to Account Settings > API Keys. 3. Ensure you are on the Generated tab. 4. Click '+ Generate Key'. 5. Enter a name in the Key identification field. 6. Click 'Generate'. 7. Copy the API token from the provided single-access link and save it securely; it is displayed only once. 8. Copy the API key identifier (appKey) from the same page.
2. Add them to .dlt/secrets.toml
[sources.vtex_source] app_key = "vtexappkey-your-account-id" app_token = "your-generated-app-token"
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 Vtex data can I load into DuckDB?
These are the Vtex endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| master_data_search | /api/dataentities/{data_entity}/search | GET | Search Master Data documents using REST-Range header. | |
| master_data_scroll | /api/dataentities/{data_entity}/scroll | GET | Scroll Master Data documents using token pagination. | |
| catalog_products | /api/catalog_system/pub/products/search | GET | Search catalog products with _from and _to pagination. | |
| storefront_roles | /api/license-manager/api/v1/roles | GET | List all storefront roles. | |
| storefront_resources | /api/license-manager/api/v1/resources | GET | List all storefront resources. |
How do I load only new Vtex records?
Vtex exposes _token on api/dataentities/{data_entity}/scroll, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.
{"name": "master_data_scroll", "endpoint": { "path": "api/dataentities/{data_entity}/scroll", "incremental": {"cursor_path": "_token", "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 Vtex pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading api/oms/pvt/orders and api/dataentities/{entity}/search from the Vtex API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def vtex_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://{accountName}.{environment}.com.br", "auth": {"type": "api_key", "api_key": api_key, "name": "X-VTEX-API-AppKey", "location": "header"}, }, "resources": [ {"name": "master_data_scroll", "endpoint": {"path": "api/dataentities/{data_entity}/scroll"}}, {"name": "catalog_products", "endpoint": {"path": "api/catalog_system/pub/products/search"}} ], } yield from rest_api_resources(config) def load_vtex_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="vtex_pipeline", destination="duckdb", dataset_name="vtex_data", ) load_info = pipeline.run(vtex_source()) print(load_info) if __name__ == "__main__": load_vtex_to_duckdb()
Run it with python vtex_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 Vtex 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("vtex_pipeline").dataset() df = data.master_data_scroll.df() print(df.head())
SQL:
SELECT * FROM vtex_data.master_data_scroll LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Vtex 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 Vtex 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 Vtex 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.
Next steps
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