Load Lucca data to DuckDB

Lucca is a platform providing a unified REST API for integrating HRIS, ERP, and internal tools with Lucca software products. Everything needed to build a working Lucca → 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 Lucca 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 Lucca 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 Lucca 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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Lucca API at a glance

These values come from the Lucca API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Lucca API?

Authentication uses OAuth 2.0 client credentials flow. Requests to the Lucca API require an 'Authorization: Bearer <access_token>' header.

1. Get your credentials

To obtain credentials for the Lucca API, you must navigate to your Lucca dashboard: Log in to your instance, click the cogwheel icon (Settings) in the top right, and select either 'Authentication, SSO and API' > 'OAuth Applications' or 'API Keys' depending on whether you are using the modern OAuth 2.0 flow (recommended) or the legacy API key method. If you do not see these options, ensure you have administrative permissions or contact your system administrator to generate them for you. For OAuth, record your 'Client ID' and 'Client Secret' immediately as the secret is only visible once. For legacy API keys, ensure you set a technical contact and select the appropriate permissions (roles) before generating the key.

2. Add them to .dlt/secrets.toml

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[sources.lucca_source]
lucca_client_id = "your_client_id_here"
lucca_client_secret = "your_client_secret_here"
lucca_api_key = "your_api_key_here"
lucca_base_url = "https://your-tenant.ilucca.net"

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 Lucca data can I load into DuckDB?

These are the Lucca endpoints dlt can load into DuckDB:

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How do I load only new Lucca records?

Lucca exposes page on lucca-api/employees, 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.

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{"name": "employees", "endpoint": {
    "path": "lucca-api/employees",
    "data_selector": "items",
    "incremental": {"cursor_path": "page", "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 Lucca pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /lucca-api/employees and /lucca-api/departments from the Lucca API into DuckDB:

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

@dlt.source
def lucca_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{account}.{environment}.{region}/lucca-api",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "employees", "endpoint": {"path": "lucca-api/employees", "data_selector": "items"}},
            {"name": "departments", "endpoint": {"path": "lucca-api/departments", "data_selector": "items"}}
        ],
    }
    yield from rest_api_resources(config)


def load_lucca_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="lucca_pipeline",
        destination="duckdb",
        dataset_name="lucca_data",
    )
    load_info = pipeline.run(lucca_source())
    print(load_info)


if __name__ == "__main__":
    load_lucca_to_duckdb()

Run it with python lucca_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 Lucca 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("lucca_pipeline").dataset()
df = data.employees.df()
print(df.head())

SQL:

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SELECT * FROM lucca_data.employees LIMIT 10;

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

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How do I deploy the Lucca 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 Lucca 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 Lucca 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