Load Directus data to DuckDB

Directus is a headless content management system that provides a dynamic, self-documenting REST API for interacting with SQL database collections. Everything needed to build a working Directus → 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 Directus 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 Directus 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 Directus 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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Directus API at a glance

These values come from the Directus API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Directus API?

Authentication is performed by including an Authorization header with a Bearer token in the request. The token is either a short-lived access token (from a login flow) or a static token generated for a specific user.

1. Get your credentials

1. Log in to the Directus Data Studio. 2. Navigate to the User Directory (accessible via the sidebar). 3. Select the user for which you want to create the token (or create a new user dedicated to this API access). 4. Scroll to the bottom of the user's settings page to find the Token section. 5. Click the Plus (+) button to generate a new static token. 6. Copy the token immediately, as it will not be displayed again. 7. Save your changes to activate the token.

2. Add them to .dlt/secrets.toml

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[sources.directus_source]
directus_api_token = "your_static_token_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 Directus data can I load into DuckDB?

These are the Directus endpoints dlt can load into DuckDB:

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How do I load only new Directus records?

Directus exposes date_updated on items/{collection}, 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": "items", "endpoint": {
    "path": "items/{collection}",
    "data_selector": "data",
    "incremental": {"cursor_path": "date_updated", "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 Directus pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /auth/login and /items/:collection from the Directus API into DuckDB:

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

@dlt.source
def directus_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "The base URL depends on the user's specific project instance, typically in the format 'https://<your-directus-instance.com>'.",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "items", "endpoint": {"path": "items/{collection}", "data_selector": "data"}},
            {"name": "activity", "endpoint": {"path": "activity", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def load_directus_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="directus_pipeline",
        destination="duckdb",
        dataset_name="directus_data",
    )
    load_info = pipeline.run(directus_source())
    print(load_info)


if __name__ == "__main__":
    load_directus_to_duckdb()

Run it with python directus_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 Directus 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("directus_pipeline").dataset()
df = data.items.df()
print(df.head())

SQL:

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SELECT * FROM directus_data.items LIMIT 10;

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

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How do I deploy the Directus 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 Directus 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 Directus 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