Load Plasmic CMS data to DuckDB

Plasmic CMS is a headless content API for managing and accessing structured data defined within Plasmic projects. Everything needed to build a working Plasmic CMS → 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 Plasmic CMS 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 Plasmic CMS 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 Plasmic CMS 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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Plasmic CMS API at a glance

These values come from the Plasmic CMS API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Plasmic CMS API?

Requests require the custom header 'x-plasmic-api-cms-tokens' with the value format 'CMS_ID:TOKEN', where TOKEN is your public or secret API token. Write operations also require a 'content-type: application/json' header.

1. Get your credentials

To obtain your API credentials in Plasmic, navigate to the Plasmic dashboard, select your workspace from the left sidebar, and click on your CMS project. Go to the 'CMS Settings' tab in the left sidebar to view your 'CMS ID', 'Public Token' (for read operations), and 'Secret Token' (for write operations).

2. Add them to .dlt/secrets.toml

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[sources.plasmic_cms_source]
plasmic_cms_id = "your_cms_id_here"
plasmic_api_token = "your_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 Plasmic CMS data can I load into DuckDB?

These are the Plasmic CMS endpoints dlt can load into DuckDB:

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How do I load only new Plasmic CMS records?

Plasmic CMS exposes q.offset on cms/databases/{CMS_ID}/tables/{CMS_MODEL_ID}/query, 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": "cms_items", "endpoint": {
    "path": "cms/databases/{CMS_ID}/tables/{CMS_MODEL_ID}/query",
    "data_selector": "rows",
    "incremental": {"cursor_path": "q.offset", "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 Plasmic CMS pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading x-plasmic-api-cms-tokens and x-plasmic-api-project-tokens from the Plasmic CMS API into DuckDB:

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

@dlt.source
def plasmic_cms_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://data.plasmic.app/api/v1/cms",
            "auth": {"type": "api_key", "api_key": api_key, "name": "x-plasmic-api-cms-tokens", "location": "header"},
        },
        "resources": [
            {"name": "cms_items", "endpoint": {"path": "cms/databases/{CMS_ID}/tables/{CMS_MODEL_ID}/query", "data_selector": "rows"}},
            {"name": "cms_count", "endpoint": {"path": "cms/databases/{CMS_ID}/tables/{CMS_MODEL_ID}/count", "data_selector": "count"}}
        ],
    }
    yield from rest_api_resources(config)


def load_plasmic_cms_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="plasmic_cms_pipeline",
        destination="duckdb",
        dataset_name="plasmic_cms_data",
    )
    load_info = pipeline.run(plasmic_cms_source())
    print(load_info)


if __name__ == "__main__":
    load_plasmic_cms_to_duckdb()

Run it with python plasmic_cms_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 Plasmic CMS 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("plasmic_cms_pipeline").dataset()
df = data.cms_items.df()
print(df.head())

SQL:

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SELECT * FROM plasmic_cms_data.cms_items LIMIT 10;

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

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How do I deploy the Plasmic CMS 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 Plasmic CMS 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 Plasmic CMS 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