Load Libsyn data to DuckDB

Libsyn provides specific integrations and a status API for managing and monitoring podcast-related data and services. Everything needed to build a working Libsyn → 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 Libsyn 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 Libsyn 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 Libsyn 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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Libsyn API at a glance

These values come from the Libsyn API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Libsyn API?

Integrations typically use OAuth2 or API keys generated via the Libsyn account dashboard. The status API does not require authentication.

1. Get your credentials

Libsyn does not provide a general-purpose public REST API for all users. API access is typically a premium feature available through Libsyn Pro or Enterprise plans. To obtain credentials: 1. Contact the Libsyn sales team or your account manager to inquire about API access for your plan. 2. Once authorized, log into your Libsyn account dashboard. 3. Navigate to the integration or developer settings section provided by your account representative. 4. Follow the instructions to generate an API key or OAuth client credentials (e.g., Client ID and Client Secret). 5. Save these credentials securely, as they will be required for your pipeline configuration. Note: The Libsyn Status API (status.libsyn.com/api/v1) is publicly accessible and does not require credentials.

2. Add them to .dlt/secrets.toml

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[sources.libsyn_source]
access_token = "your_api_key_or_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 Libsyn data can I load into DuckDB?

These are the Libsyn endpoints dlt can load into DuckDB:

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How do I load only new Libsyn records?

The Libsyn 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": "components", "endpoint": {
    "path": "api/v1/components",
    # 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 Libsyn pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading components and notices from the Libsyn API into DuckDB:

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

@dlt.source
def libsyn_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://status.libsyn.com/api/v1",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "components", "endpoint": {"path": "api/v1/components", "data_selector": "components"}},
            {"name": "notices", "endpoint": {"path": "api/v1/notices", "data_selector": "notices"}}
        ],
    }
    yield from rest_api_resources(config)


def load_libsyn_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="libsyn_pipeline",
        destination="duckdb",
        dataset_name="libsyn_data",
    )
    load_info = pipeline.run(libsyn_source())
    print(load_info)


if __name__ == "__main__":
    load_libsyn_to_duckdb()

Run it with python libsyn_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 Libsyn 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("libsyn_pipeline").dataset()
df = data.notices.df()
print(df.head())

SQL:

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SELECT * FROM libsyn_data.notices LIMIT 10;

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

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How do I deploy the Libsyn 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 Libsyn 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 Libsyn 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