Load DocuSeal data to DuckDB

DocuSeal is an open-source platform for building document signing workflows and managing digital signatures. Everything needed to build a working DocuSeal → 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 DocuSeal 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 DocuSeal 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 DocuSeal 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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DocuSeal API at a glance

These values come from the DocuSeal API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the DocuSeal API?

DocuSeal authenticates requests by including an API key in the 'X-Auth-Token' header.

1. Get your credentials

1. Log in to your DocuSeal account at console.docuseal.com. 2. Click on your profile initials/menu in the top-right corner and navigate to 'Console'. 3. In the left-hand sidebar, select 'API'. 4. (Optional) Toggle 'Test Mode' in the top-right if you are developing in the test environment. 5. Click the 'Copy' button to generate or copy your API key. Note: Keep this key secure as it provides full access to your account data.

2. Add them to .dlt/secrets.toml

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[sources.docuseal_source]
api_key = "your_api_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 DocuSeal data can I load into DuckDB?

These are the DocuSeal endpoints dlt can load into DuckDB:

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How do I load only new DocuSeal records?

DocuSeal exposes after on submissions, 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": "submissions", "endpoint": {
    "path": "submissions",
    "data_selector": "data",
    "incremental": {"cursor_path": "after", "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 DocuSeal pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /submissions and /templates from the DocuSeal API into DuckDB:

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

@dlt.source
def docuseal_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.docuseal.com",
            "auth": {"type": "api_key", "api_key": api_key, "name": "X-Auth-Token", "location": "header"},
        },
        "resources": [
            {"name": "submissions", "endpoint": {"path": "submissions", "data_selector": "data"}},
            {"name": "submitters", "endpoint": {"path": "submitters", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def load_docuseal_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="docuseal_pipeline",
        destination="duckdb",
        dataset_name="docuseal_data",
    )
    load_info = pipeline.run(docuseal_source())
    print(load_info)


if __name__ == "__main__":
    load_docuseal_to_duckdb()

Run it with python docuseal_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 DocuSeal 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("docuseal_pipeline").dataset()
df = data.submissions.df()
print(df.head())

SQL:

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SELECT * FROM docuseal_data.submissions LIMIT 10;

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

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How do I deploy the DocuSeal 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 DocuSeal 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 DocuSeal 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