Load ConvertKit data to DuckDB

Kit (formerly ConvertKit) is a creator email marketing platform offering a REST API for managing subscribers, sequences, and broadcasts. Everything needed to build a working ConvertKit → 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 ConvertKit 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 ConvertKit 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 ConvertKit 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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ConvertKit API at a glance

These values come from the ConvertKit API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the ConvertKit API?

The API supports two authentication mechanisms: an API Key (sent via the X-Kit-Api-Key header) for account-level automation, and OAuth 2.0 (sent as a Bearer token in the Authorization header) for application-level integration.

1. Get your credentials

To obtain API credentials for Kit (formerly ConvertKit), log in to your account and navigate to the Developer settings page (typically found via account settings). For V4 API access, which is recommended for modern integrations, locate the 'V4 Keys' section, click 'Add a new key', provide an internal name, and securely save the generated API key immediately as it will not be displayed again. For older third-party integrations, you can generate or retrieve a V3 API key and API Secret from the 'V3 API' section on the same page.

2. Add them to .dlt/secrets.toml

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[sources.convertkit_source]
api_key = "your_v4_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 ConvertKit data can I load into DuckDB?

These are the ConvertKit endpoints dlt can load into DuckDB:

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How do I load only new ConvertKit records?

ConvertKit exposes after on v4/subscribers, 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": "subscribers", "endpoint": {
    "path": "v4/subscribers",
    "data_selector": "subscribers",
    "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 ConvertKit pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading For the V4 API, the most commonly used endpoints are /v4/account and /v4/subscribers. For the legacy V3 API, common endpoints include /v3/subscribers and /v3/tags. from the ConvertKit API into DuckDB:

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

@dlt.source
def convertkit_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.kit.com/v4",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "subscribers", "endpoint": {"path": "v4/subscribers", "data_selector": "subscribers"}},
            {"name": "broadcasts", "endpoint": {"path": "v4/broadcasts", "data_selector": "broadcasts"}}
        ],
    }
    yield from rest_api_resources(config)


def load_convertkit_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="convertkit_pipeline",
        destination="duckdb",
        dataset_name="convertkit_data",
    )
    load_info = pipeline.run(convertkit_source())
    print(load_info)


if __name__ == "__main__":
    load_convertkit_to_duckdb()

Run it with python convertkit_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 ConvertKit 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("convertkit_pipeline").dataset()
df = data.subscribers.df()
print(df.head())

SQL:

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SELECT * FROM convertkit_data.subscribers LIMIT 10;

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

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How do I deploy the ConvertKit 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 ConvertKit 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 ConvertKit 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