Load Sumsub data to DuckDB
Build a Sumsub to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Sumsub API base URL, auth, endpoints, and incremental loading.
Sumsub is a full-stack verification platform providing REST APIs for identity and business verification, AML screening, and fraud monitoring. Everything needed to build a working Sumsub → 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 Sumsub to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from Sumsub 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 Sumsub 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.
Sumsub API at a glance
| Base URL | https://api.sumsub.com |
| Example endpoint | GET resources/auditTrailEvents/list |
| Records found at | items |
| Authentication | all requests require X-App-Token, X-App-Access-Ts, and X-App-Access-Sig headers for HMAC-SHA256 request signing — sent in the X-App-Token header, prefixed "" |
| Pagination | Cursor-based via forwardMarker, next cursor at forwardMarker, page size via limit (default 20, max 1000). Uses forward-only cursor pagination: omit forwardMarker in the initial request; if forwardMarker is returned (string), send it as-is in subsequent requests to fetch the next page. If forwardMarker is absent or null, you have reached the last page. Page size is controlled by the query parameter limit (allowed 1–1000). |
| Incremental field | forwardMarker |
| Record id | id |
| API reference | https://docs.sumsub.com/reference/authentication |
These values come from the Sumsub API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the Sumsub API?
Authentication requires three headers: X-App-Token (the app token), X-App-Access-Ts (current Unix timestamp in seconds, UTC), and X-App-Access-Sig (a lowercase HEX HMAC-SHA256 signature). The signature is generated using the secret key on a concatenation of the timestamp, uppercase HTTP method, URI (with query params), and raw request body.
1. Get your credentials
- Log in to your Sumsub dashboard. 2. Navigate to the 'Dev space' or 'Integration' section (depending on your account dashboard version). 3. Select 'App Tokens'. 4. Click 'Generate app token'. 5. Enter a preferred name for the token and configure the required permissions. 6. Click 'Generate app token'. 7. Save the App Token and Secret Key immediately in a secure location, as they are displayed only once.
2. Add them to .dlt/secrets.toml
[sources.sumsub_source] api_key = "REPLACE_ME"
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 Sumsub data can I load into DuckDB?
These are the Sumsub endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| audit_trail_events | /resources/auditTrailEvents/list | GET | Retrieve audit trail events using forward-only cursor pagination. | |
| applicant_actions | /resources/applicantActions/-;applicantId={applicantId} | GET | list.items | List paginated applicant actions. |
| questionnaires | /resources/api/questionnaires/list | GET | list.items | Retrieve a list of all questionnaires. |
| applicant_action | /resources/applicantActions/{actionId}/one | GET | Get a single applicant action (check result). | |
| applicant_data | /resources/applicants/{applicantId}/one | GET | Get applicant data for a specific applicant. |
How do I load only new Sumsub records?
Sumsub exposes forwardMarker on resources/auditTrailEvents/list, 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": "audit_trail_events", "endpoint": { "path": "resources/auditTrailEvents/list", "data_selector": "items", "incremental": {"cursor_path": "forwardMarker", "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 Sumsub pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading POST /resources/accessTokens and GET /resources/applicants/{applicantId}/one from the Sumsub API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def sumsub_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.sumsub.com", "auth": {"type": "api_key", "api_key": api_key, "name": "X-App-Token", "location": "header"}, }, "resources": [ {"name": "audit_trail_events", "endpoint": {"path": "resources/auditTrailEvents/list", "data_selector": "items"}}, {"name": "questionnaires", "endpoint": {"path": "resources/api/questionnaires/list", "data_selector": "list.items"}} ], } yield from rest_api_resources(config) def load_sumsub_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="sumsub_pipeline", destination="duckdb", dataset_name="sumsub_data", ) load_info = pipeline.run(sumsub_source()) print(load_info) if __name__ == "__main__": load_sumsub_to_duckdb()
Run it with python sumsub_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 Sumsub 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("sumsub_pipeline").dataset() df = data.audit_trail_events.df() print(df.head())
SQL:
SELECT * FROM sumsub_data.audit_trail_events LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the Sumsub 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 Sumsub 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 Sumsub 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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