Load Arkose Labs data to DuckDB

Arkose Labs provides fraud prevention and bot management services via its Verify and Edge APIs. Everything needed to build a working Arkose Labs → 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.

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Build your Arkose Labs to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from Arkose Labs 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 Arkose Labs 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.

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Arkose Labs API at a glance

These values come from the Arkose Labs API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Arkose Labs API?

The API uses a private key passed as a field in the JSON request body (not via HTTP headers) for server-side verification. The header 'Content-Type: application/json' is required for POST requests.

1. Get your credentials

To obtain your API credentials, log in to the Arkose Labs Command Center, navigate to the Settings entry in the left menu, and select the Keys sub-entry to access your public and private key pair. If you do not have access to the Command Center or the keys, contact your Arkose Customer Success Manager (CSM).

2. Add them to .dlt/secrets.toml

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[sources.arkose_labs_source]
private_key = "your_private_key_here"
public_key = "your_public_key_here"

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.

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What Arkose Labs data can I load into DuckDB?

These are the Arkose Labs endpoints dlt can load into DuckDB:

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How do I load only new Arkose Labs records?

The Arkose Labs 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.

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{"name": "verify", "endpoint": {
    "path": "api/v4/verify/",
    # 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.

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What does the generated Arkose Labs pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading verify and edge from the Arkose Labs API into DuckDB:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def arkose_labs_source(private_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<company>-verify.arkoselabs.com/api/v4/verify/",
            "auth": {"type": "bearer", "token": private_key},
        },
        "resources": [
            {"name": "verify", "endpoint": {"path": "api/v4/verify/"}},
            {"name": "edge", "endpoint": {"path": "api/edge/v1/"}}
        ],
    }
    yield from rest_api_resources(config)


def load_arkose_labs_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="arkose_labs_pipeline",
        destination="duckdb",
        dataset_name="arkose_labs_data",
    )
    load_info = pipeline.run(arkose_labs_source())
    print(load_info)


if __name__ == "__main__":
    load_arkose_labs_to_duckdb()

Run it with python arkose_labs_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query Arkose Labs 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):

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import dlt

data = dlt.pipeline("arkose_labs_pipeline").dataset()
df = data.verify.df()
print(df.head())

SQL:

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SELECT * FROM arkose_labs_data.verify LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the Arkose Labs 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 Arkose Labs loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Arkose Labs data to?

dlt loads into any of these — only the destination argument changes:

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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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack