Load Stripe - Main API data to Snowflake

Stripe is a platform for processing payments and managing financial data through RESTful API services. Everything needed to build a working Stripe - Main API → Snowflake 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 Stripe - Main API to Snowflake pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

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 Stripe - Main API 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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Stripe - Main API API at a glance

These values come from the Stripe - Main API API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Stripe - Main API API?

Stripe authenticates requests using HTTP Basic Auth (API key as username, no password) or Bearer authentication (Authorization: Bearer ). Requests for V2 endpoints specifically require the Stripe-Version header.

1. Get your credentials

1. Log in to your Stripe Dashboard (dashboard.stripe.com). 2. Navigate to Developers in the top navigation menu. 3. Click API keys from the sidebar. 4. Under the Standard keys section, click Reveal test key (or Create secret key if you do not have one) to display your secret API key. 5. Copy the key immediately, as it cannot be retrieved again. Ensure the key begins with sk_test_ for development or sk_live_ for production.

2. Add them to .dlt/secrets.toml

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[sources.stripe_main_api_source]
stripe_secret_key = "sk_test_..." # Replace with your actual Stripe secret API key

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 Stripe - Main API data can I load into Snowflake?

These are the Stripe - Main API endpoints dlt can load into Snowflake:

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How do I load only new Stripe - Main API records?

Stripe - Main API exposes starting_after on v1/customers, 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": "customers", "endpoint": {
    "path": "v1/customers",
    "data_selector": "data",
    "incremental": {"cursor_path": "starting_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 Stripe - Main API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /v1/charges and /v1/invoices from the Stripe - Main API API into Snowflake:

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

@dlt.source
def stripe_main_api_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.stripe.com",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "customers", "endpoint": {"path": "v1/customers", "data_selector": "data"}},
            {"name": "prices", "endpoint": {"path": "v1/prices", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def load_stripe_main_api_to_snowflake() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="stripe_main_api_pipeline",
        destination="snowflake",
        dataset_name="stripe_main_api_data",
    )
    load_info = pipeline.run(stripe_main_api_source())
    print(load_info)


if __name__ == "__main__":
    load_stripe_main_api_to_snowflake()

Run it with uv run python stripe_main_api_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 Stripe - Main API data in Snowflake?

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("stripe_main_api_pipeline").dataset()
df = data.customers.df()
print(df.head())

SQL:

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SELECT * FROM stripe_main_api_data.customers LIMIT 10;

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

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How do I deploy the Stripe - Main API to Snowflake 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 Stripe - Main API 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 Stripe - Main API 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